diff --git a/source/isaaclab/changelog.d/jichuanh-id-mask.added.rst b/source/isaaclab/changelog.d/jichuanh-id-mask.added.rst
new file mode 100644
index 000000000000..9dfc5d1942ba
--- /dev/null
+++ b/source/isaaclab/changelog.d/jichuanh-id-mask.added.rst
@@ -0,0 +1,4 @@
+* Added :func:`~isaaclab.utils.warp.utils.resolve_ids`, which resolves an index selection given as ids or as a
+  boolean mask to ids on a device, as :func:`~isaaclab.utils.warp.utils.resolve_1d_mask` does to a mask.
+* Added :func:`~isaaclab.utils.warp.utils.write_2d_with_mask`, which writes 2-D data or one scalar into a Warp array
+  where an environment mask and an item mask are both true, launching over the mask lengths.
diff --git a/source/isaaclab/changelog.d/jichuanh-id-mask.changed.rst b/source/isaaclab/changelog.d/jichuanh-id-mask.changed.rst
new file mode 100644
index 000000000000..a94a9dba2c3a
--- /dev/null
+++ b/source/isaaclab/changelog.d/jichuanh-id-mask.changed.rst
@@ -0,0 +1,14 @@
+* Changed the env selection helpers of :class:`~isaaclab.utils.wrench_composer.WrenchComposer`,
+  :class:`~isaaclab.sensors.SensorBase` and :class:`~isaaclab.sensors.Camera` to resolve ``env_ids`` and ``env_mask``
+  through :func:`~isaaclab.utils.warp.utils.resolve_ids` and :func:`~isaaclab.utils.warp.utils.resolve_1d_mask`.
+  Any integer sequence and slices with a negative step are accepted, ids on another device are moved to the owner's
+  device, and a :class:`~isaaclab.utils.warp.ProxyArray` is rejected with a :class:`TypeError`. The
+  :class:`~isaaclab.sensors.Camera` now rejects floating-point ``env_ids`` with a :class:`TypeError` and
+  multi-dimensional ``env_ids`` with a :class:`ValueError` instead of casting and flattening them.
+* Changed :class:`~isaaclab.utils.wrench_composer.WrenchComposer` to resolve ``body_ids`` through
+  :func:`~isaaclab.utils.warp.utils.resolve_ids` as well, so slices other than ``slice(None)`` are accepted.
+* Changed :func:`~isaaclab.utils.warp.utils.resolve_1d_mask` to make ``scratch_mask`` optional for callers that never
+  pass ids. Ids without a ``scratch_mask`` raise a :class:`ValueError`.
+* Changed :func:`~isaaclab.utils.warp.utils.resolve_1d_mask` to copy a Warp mask or Warp ids on another device to
+  ``device``, to accept 64-bit Warp ids and slices with a negative step, and to accept a boolean torch mask on
+  ``device``, including ``"cuda"`` for the current CUDA device, inside a CUDA graph capture.
diff --git a/source/isaaclab/changelog.d/jichuanh-id-mask.fixed.rst b/source/isaaclab/changelog.d/jichuanh-id-mask.fixed.rst
new file mode 100644
index 000000000000..9ed262f73ec2
--- /dev/null
+++ b/source/isaaclab/changelog.d/jichuanh-id-mask.fixed.rst
@@ -0,0 +1,2 @@
+* Fixed the ``write_nodal_*_to_sim_mask`` methods of :class:`~isaaclab.assets.BaseDeformableObject`, which the
+  OVPhysX deformable object inherits, raising a :class:`RuntimeError` whenever ``env_mask`` was given.
diff --git a/source/isaaclab/changelog.d/jichuanh-id-mask.minor b/source/isaaclab/changelog.d/jichuanh-id-mask.minor
new file mode 100644
index 000000000000..e69de29bb2d1
diff --git a/source/isaaclab/isaaclab/assets/deformable_object/base_deformable_object.py b/source/isaaclab/isaaclab/assets/deformable_object/base_deformable_object.py
index 0542a460af48..4467403b79cf 100644
--- a/source/isaaclab/isaaclab/assets/deformable_object/base_deformable_object.py
+++ b/source/isaaclab/isaaclab/assets/deformable_object/base_deformable_object.py
@@ -15,6 +15,7 @@
 
 from ...utils import math as math_utils
 from ...utils.warp import ProxyArray
+from ...utils.warp.utils import resolve_ids
 from ..asset_base import AssetBase
 
 if TYPE_CHECKING:
@@ -200,6 +201,9 @@ def write_nodal_kinematic_target_to_sim_index(
 
     """
     Operations - Write to simulation (mask variants).
+
+    These convert the mask to ids, which waits for the device, and call the index variants.
+    Backends with a mask write path override them.
     """
 
     def write_nodal_state_to_sim_mask(
@@ -214,10 +218,7 @@ def write_nodal_state_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 6).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_state_to_sim_index(nodal_state, env_ids=env_ids, full_data=True)
 
     def write_nodal_pos_to_sim_mask(
@@ -232,10 +233,7 @@ def write_nodal_pos_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 3).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_pos_to_sim_index(nodal_pos, env_ids=env_ids, full_data=True)
 
     def write_nodal_velocity_to_sim_mask(
@@ -250,10 +248,7 @@ def write_nodal_velocity_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 3).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_velocity_to_sim_index(nodal_vel, env_ids=env_ids, full_data=True)
 
     def write_nodal_kinematic_target_to_sim_mask(
@@ -268,10 +263,7 @@ def write_nodal_kinematic_target_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 4).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_kinematic_target_to_sim_index(targets, env_ids=env_ids, full_data=True)
 
     """
diff --git a/source/isaaclab/isaaclab/sensors/camera/camera.py b/source/isaaclab/isaaclab/sensors/camera/camera.py
index d052dd59aa73..b1e577520bbb 100644
--- a/source/isaaclab/isaaclab/sensors/camera/camera.py
+++ b/source/isaaclab/isaaclab/sensors/camera/camera.py
@@ -26,6 +26,7 @@
     quat_from_matrix,
 )
 from ...utils.warp import ProxyArray
+from ...utils.warp.utils import resolve_ids
 from ..sensor_base import SensorBase
 from .camera_data import CameraData, RenderBufferKind
 
@@ -1028,27 +1029,7 @@ def _resolve_env_ids_wp(self, env_ids: Sequence[int] | torch.Tensor | wp.array |
         """Resolve camera indices to a Warp ``int32`` array."""
         if env_ids is None:
             return None
-        if isinstance(env_ids, wp.array):
-            if env_ids.dtype != wp.int32:
-                raise TypeError(f"Unsupported wp.array dtype for env_ids: {env_ids.dtype}. Expected wp.int32.")
-            if env_ids.ndim != 1:
-                raise ValueError("Warp camera indices must be a one-dimensional array.")
-            if str(env_ids.device) == str(self._device):
-                return env_ids
-            return env_ids.to(self._device)
-        elif isinstance(env_ids, torch.Tensor):
-            env_ids = env_ids.to(device=self._device, dtype=torch.int32).reshape(-1)
-            if not env_ids.is_contiguous():
-                env_ids = env_ids.contiguous()
-            return wp.from_torch(env_ids, dtype=wp.int32)
-        elif isinstance(env_ids, slice) and (env_ids.step or 1) > 0:
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        elif isinstance(env_ids, slice):
-            # Torch cannot slice with a negative step.
-            env_ids = np.arange(self._view.count, dtype=np.int32)[env_ids]
-        else:
-            env_ids = np.asarray(env_ids, dtype=np.int32).reshape(-1)
-        return wp.array(env_ids, dtype=wp.int32, device=self._device)
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self._device, dtype=wp.int32)
 
     def _env_mask_has_any(self, env_mask: wp.array) -> bool:
         """Return whether the mask selects any camera."""
diff --git a/source/isaaclab/isaaclab/sensors/sensor_base.py b/source/isaaclab/isaaclab/sensors/sensor_base.py
index 5bcec23eb91e..f0e39055540d 100644
--- a/source/isaaclab/isaaclab/sensors/sensor_base.py
+++ b/source/isaaclab/isaaclab/sensors/sensor_base.py
@@ -29,7 +29,7 @@
 from ..physics import PhysicsEvent, PhysicsManager
 from ..sim.utils.queries import get_first_matching_ancestor_prim
 from ..sim.utils.transforms import resolve_prim_pose
-from ..utils import index_fill_
+from ..utils.warp.utils import resolve_1d_mask
 from .kernels import invalidate_buffers_kernel, reset_envs_kernel, update_outdated_envs_kernel, update_timestamp_kernel
 
 if TYPE_CHECKING:
@@ -506,14 +506,9 @@ def _resolve_indices_and_mask(
         self, env_ids: Sequence[int] | None = None, env_mask: wp.array | None = None
     ) -> wp.array:
         """Resolve environment indices to a warp array and mask."""
-        if (env_ids is None or env_ids == slice(None)) and env_mask is None:
-            return self._ALL_ENV_MASK
-        elif env_mask is not None:
-            return env_mask
-        else:
-            self._reset_mask.zero_()
-            index_fill_(self._reset_mask_torch, env_ids, True)
-            return self._reset_mask
+        return resolve_1d_mask(
+            ids=env_ids, mask=env_mask, all_mask=self._ALL_ENV_MASK, device=self._device, scratch_mask=self._reset_mask
+        )
 
     def _resolve_rigid_body_ancestor_expr(
         self,
diff --git a/source/isaaclab/isaaclab/utils/warp/kernels.py b/source/isaaclab/isaaclab/utils/warp/kernels.py
index 3d046abe2bba..bc9b63d11339 100644
--- a/source/isaaclab/isaaclab/utils/warp/kernels.py
+++ b/source/isaaclab/isaaclab/utils/warp/kernels.py
@@ -5,6 +5,7 @@
 
 """Custom kernels for warp."""
 
+import functools
 from typing import Any
 
 import torch
@@ -780,3 +781,61 @@ def gather_subtract_2d(
 def gather_subtract_2d_kernel(env_ids: "wp.array | torch.Tensor", item_ids: "wp.array | torch.Tensor") -> wp.Kernel:
     """Select the gather-subtract worker for the selector dtypes."""
     return _GATHER_SUBTRACT_2D_DISPATCHER.select(env_ids, item_ids)
+
+
+##
+# Masked writes.
+##
+
+
+@wp.kernel
+def write_2d_data_to_buffer_with_mask(
+    in_data: wp.array2d(dtype=Any),
+    env_mask: wp.array(dtype=wp.bool),
+    item_mask: wp.array(dtype=wp.bool),
+    out_data: wp.array2d(dtype=Any),
+):
+    """Write 2D data to a buffer where both the environment and the item mask are set.
+
+    Args:
+        in_data: Input array containing data for every environment and item. Shape is (num_envs, num_items).
+        env_mask: Input array of environment mask. Shape is (num_envs,).
+        item_mask: Input array of item mask. Shape is (num_items,).
+        out_data: Output array where data is written. Shape is (num_envs, num_items).
+    """
+    i, j = wp.tid()
+    if env_mask[i] and item_mask[j]:
+        out_data[i, j] = in_data[i, j]
+
+
+@functools.cache
+def write_2d_data_to_buffer_with_mask_kernel(dtype: type) -> wp.Kernel:
+    """Select the masked 2-D buffer writer for the buffer dtype."""
+    array = wp.array2d(dtype=dtype)
+    return wp.overload(write_2d_data_to_buffer_with_mask, {"in_data": array, "out_data": array})
+
+
+@wp.kernel
+def fill_2d_buffer_with_mask(
+    value: Any,
+    env_mask: wp.array(dtype=wp.bool),
+    item_mask: wp.array(dtype=wp.bool),
+    out_data: wp.array2d(dtype=Any),
+):
+    """Write one value to a buffer where both the environment and the item mask are set.
+
+    Args:
+        value: Value written to every selected entry.
+        env_mask: Input array of environment mask. Shape is (num_envs,).
+        item_mask: Input array of item mask. Shape is (num_items,).
+        out_data: Output array where the value is written. Shape is (num_envs, num_items).
+    """
+    i, j = wp.tid()
+    if env_mask[i] and item_mask[j]:
+        out_data[i, j] = value
+
+
+@functools.cache
+def fill_2d_buffer_with_mask_kernel(dtype: type) -> wp.Kernel:
+    """Select the masked 2-D buffer fill for the buffer dtype."""
+    return wp.overload(fill_2d_buffer_with_mask, {"value": dtype, "out_data": wp.array2d(dtype=dtype)})
diff --git a/source/isaaclab/isaaclab/utils/warp/utils.py b/source/isaaclab/isaaclab/utils/warp/utils.py
index afd31e9c1b38..cb1197803a0d 100644
--- a/source/isaaclab/isaaclab/utils/warp/utils.py
+++ b/source/isaaclab/isaaclab/utils/warp/utils.py
@@ -11,6 +11,9 @@
 import torch
 import warp as wp
 
+from .kernels import fill_2d_buffer_with_mask_kernel, write_2d_data_to_buffer_with_mask_kernel
+from .proxy_array import ProxyArray
+
 ##
 # Mask resolution - ids/mask to warp boolean mask.
 ##
@@ -30,47 +33,54 @@ def resolve_1d_mask(
     ids: Sequence[int] | slice | torch.Tensor | wp.array | None = None,
     mask: wp.array | torch.Tensor | None = None,
     all_mask: wp.array,
-    scratch_mask: wp.array,
+    scratch_mask: wp.array | None = None,
     device: str,
 ) -> wp.array:
     """Resolve ids/mask into a warp boolean mask.
 
     Callers provide pre-allocated ``all_mask`` (all-True) and ``scratch_mask`` (reusable
-    work buffer) so this function never allocates.
+    work buffer), so nothing is allocated for ``None``, a slice, a boolean mask on ``device``
+    or contiguous ``wp.int32`` ids on ``device``. Other selections are copied to ``device`` first.
 
     Args:
         ids: Index ids. Accepts ``Sequence[int]``, ``slice``, ``torch.Tensor``,
-            ``wp.array(dtype=wp.int32)``, or ``None`` (all elements).
-        mask: Direct boolean mask. ``wp.array`` is returned as-is;
+            ``wp.array`` of 32-bit or 64-bit integers, or ``None`` (all elements).
+        mask: Direct boolean mask. ``wp.array`` is returned as-is, or copied when on another device;
             ``torch.Tensor`` is converted.
         all_mask: Pre-allocated all-True mask returned when both *ids* and *mask*
             are ``None``.
         scratch_mask: Pre-allocated scratch buffer populated in-place when *ids*
-            are provided. Not re-entrant (shared buffer).
+            are provided. Not re-entrant (shared buffer). Defaults to None, for callers
+            that never pass *ids*.
         device: Warp device string (e.g. ``"cuda:0"``).
 
     Returns:
         A ``wp.array(dtype=wp.bool)`` mask.
+
+    Raises:
+        ValueError: If *ids* select a subset of elements and no ``scratch_mask`` is given.
     """
     # Normalize slice(None) to None so the capture guard treats it identically to ids=None.
     if isinstance(ids, slice) and ids == slice(None):
         ids = None
 
     if wp.get_device().is_capturing:
-        if ids is not None or (mask is not None and not isinstance(mask, wp.array)):
+        if ids is not None or (mask is not None and _mask_needs_copy(mask, device)):
             raise RuntimeError(
-                "resolve_1d_mask is only capturable when mask is a wp.array or both ids and mask are None."
+                "resolve_1d_mask is only capturable when ids are None and mask is None or a boolean mask on device."
             )
 
     # --- Direct mask input ---
     if mask is not None:
         if isinstance(mask, wp.array):
+            if mask.device != wp.get_device(device):
+                mask = wp.clone(mask, device=device)
             return mask
         if isinstance(mask, torch.Tensor):
             if mask.dtype != torch.bool:
                 mask = mask.to(dtype=torch.bool)
-            if str(mask.device) != device:
-                mask = mask.to(device)
+            if str(mask.device) != str(wp.get_device(device)):
+                mask = mask.to(wp.device_to_torch(device))
             return wp.from_torch(mask, dtype=wp.bool)
         raise TypeError(f"Unsupported mask type: {type(mask)}")
 
@@ -78,9 +88,16 @@ def resolve_1d_mask(
     if ids is None:
         return all_mask
 
+    if scratch_mask is None:
+        raise ValueError("resolve_1d_mask needs a scratch_mask to write ids into.")
+
     if isinstance(ids, slice):
+        # a mask has no order, so a negative step selects what its reversed, positive-step range selects
+        selected = range(*ids.indices(scratch_mask.shape[0]))
+        if selected.step < 0:
+            selected = selected[::-1]
         scratch_mask.zero_()
-        wp.to_torch(scratch_mask)[ids] = True
+        wp.to_torch(scratch_mask)[selected.start : selected.stop : selected.step] = True
         return scratch_mask
 
     # --- Normalize to concrete type ---
@@ -103,9 +120,9 @@ def resolve_1d_mask(
     elif isinstance(ids, wp.array):
         if ids.shape[0] == 0:
             return scratch_mask
-        if ids.dtype != wp.int32:
-            raise TypeError(f"Unsupported wp.array dtype for ids: {ids.dtype}. Expected wp.int32 index array.")
-        ids_wp = ids
+        if ids.device != wp.get_device(device):
+            ids = ids.to(device)
+        ids_wp = _ids_as_dtype(ids, wp.int32)
     else:
         if len(ids) == 0:
             return scratch_mask
@@ -115,6 +132,145 @@ def resolve_1d_mask(
     return scratch_mask
 
 
+def _mask_needs_copy(mask: wp.array | torch.Tensor, device: str) -> bool:
+    """Whether :func:`resolve_1d_mask` casts or copies ``mask``, which a graph capture cannot record."""
+    if isinstance(mask, wp.array):
+        return mask.device != wp.get_device(device)
+    if isinstance(mask, torch.Tensor):
+        return mask.dtype != torch.bool or str(mask.device) != str(wp.get_device(device))
+    return True
+
+
+##
+# Masked writes.
+##
+
+
+def write_2d_with_mask(
+    data: float | torch.Tensor | wp.array,
+    env_mask: wp.array,
+    item_mask: wp.array,
+    out: wp.array,
+    device: str,
+) -> None:
+    """Write ``data`` into ``out`` where both masks are true, launching over the mask lengths.
+
+    A mask shorter than ``out`` writes only the rows or columns it covers. Callers resolve the masks and check the
+    data shape.
+
+    Args:
+        data: Values of shape ``(env_mask.shape[0], item_mask.shape[0])`` in the dtype of ``out``, as a ``wp.array``
+            or a ``torch.Tensor`` with the dtype's trailing dimensions, or one scalar for every selected entry.
+        env_mask: Boolean mask over the first dimension of ``out``.
+        item_mask: Boolean mask over the second dimension of ``out``.
+        out: Output array.
+        device: Warp device string (e.g. ``"cuda:0"``).
+    """
+    if isinstance(data, (int, float)):
+        kernel = fill_2d_buffer_with_mask_kernel(out.dtype)
+    else:
+        if isinstance(data, torch.Tensor) and data.ndim > 2:
+            # a vector-typed kernel argument needs contiguous components
+            data = data.contiguous()
+        kernel = write_2d_data_to_buffer_with_mask_kernel(out.dtype)
+    wp.launch(
+        kernel,
+        dim=(env_mask.shape[0], item_mask.shape[0]),
+        inputs=[data, env_mask, item_mask],
+        outputs=[out],
+        device=device,
+    )
+
+
+##
+# Id resolution - ids/mask to ids.
+##
+
+
+def resolve_ids(
+    *,
+    ids: Sequence[int] | slice | torch.Tensor | wp.array | None = None,
+    mask: wp.array | torch.Tensor | None = None,
+    all_ids: wp.array,
+    device: str,
+    dtype: type | None = None,
+) -> wp.array | torch.Tensor:
+    """Resolve ids/mask into ids on ``device``. The mask takes precedence over the ids.
+
+    Args:
+        ids: Index ids. Accepts ``Sequence[int]``, ``slice``, ``torch.Tensor``, ``wp.array``,
+            or ``None`` (all elements). Tensors and warp arrays keep their integer dtype
+            unless ``dtype`` is given. Pass ids from ``find_*(as_proxy=True)`` as ``.warp`` or ``.torch``.
+        mask: Boolean mask. Its ids are found with :func:`torch.nonzero`, which waits for
+            the device.
+        all_ids: Pre-allocated ids of every element, returned as-is when *ids* and *mask*
+            select every element.
+        device: Warp device string (e.g. ``"cuda:0"``).
+        dtype: Warp integer dtype the ids must have, for callers whose kernels take one
+            index dtype. The ids are then a contiguous 1-D ``wp.array`` of this dtype.
+            Defaults to None: a mask resolves to an int64 ``torch.Tensor``, and ids keep
+            their type and dtype.
+
+    Returns:
+        ``all_ids``, a ``torch.Tensor`` or a ``wp.array`` of ids on ``device``.
+
+    Raises:
+        TypeError: If *ids* is a :class:`ProxyArray`, which is output-only, *mask* is
+            neither a ``wp.array`` nor a ``torch.Tensor``, or ``dtype`` is given and the
+            ids are not 32-bit or 64-bit integers.
+        ValueError: If ``dtype`` is given and the ids are not one-dimensional.
+    """
+    if mask is not None:
+        if isinstance(mask, wp.array):
+            mask = wp.to_torch(mask)
+        elif not isinstance(mask, torch.Tensor):
+            raise TypeError(f"Unsupported mask type: {type(mask)}")
+        ids = torch.nonzero(mask.to(wp.device_to_torch(device))).squeeze(-1)
+    else:
+        ids = _ids_on_device(ids, all_ids, device)
+    return ids if dtype is None else _ids_as_dtype(ids, dtype)
+
+
+def _ids_on_device(
+    ids: Sequence[int] | slice | torch.Tensor | wp.array | None, all_ids: wp.array, device: str
+) -> wp.array | torch.Tensor:
+    """Ids on ``device``, keeping the dtype of tensors and warp arrays; lists and slices become ``wp.int32``."""
+    if isinstance(ids, torch.Tensor):
+        return ids if str(ids.device) == str(wp.get_device(device)) else ids.to(wp.device_to_torch(device))
+    if ids is None:
+        return all_ids
+    if isinstance(ids, wp.array):
+        return ids if ids.device == wp.get_device(device) else ids.to(device)
+    if isinstance(ids, ProxyArray):
+        raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
+    if isinstance(ids, slice):
+        if ids == slice(None):
+            return all_ids
+        start, stop, step = ids.indices(all_ids.shape[0])
+        if step > 0:
+            # a strided view of the caller's all-ids, no copy
+            return wp.from_torch(wp.to_torch(all_ids)[start:stop:step])
+        return wp.array(list(range(start, stop, step)), dtype=wp.int32, device=device)
+    return wp.array(list(ids), dtype=wp.int32, device=device)
+
+
+def _ids_as_dtype(ids: wp.array | torch.Tensor, dtype: type) -> wp.array:
+    """``ids`` as a contiguous 1-D ``wp.array`` of ``dtype`` on their device."""
+    if dtype not in (wp.int32, wp.int64):
+        raise TypeError(f"Unsupported id dtype: {dtype}. Expected wp.int32 or wp.int64.")
+    if ids.ndim != 1:
+        raise ValueError(f"Ids must be a one-dimensional array, got {ids.ndim} dimensions.")
+    if isinstance(ids, wp.array):
+        if ids.dtype == dtype and ids.is_contiguous:
+            return ids
+        if ids.dtype not in (wp.int32, wp.int64):
+            raise TypeError(f"Warp ids must be 32-bit or 64-bit signed integers, got {ids.dtype}.")
+        ids = wp.to_torch(ids)
+    elif ids.dtype.is_floating_point or ids.dtype.is_complex or ids.dtype == torch.bool:
+        raise TypeError(f"Ids must be integers, got {ids.dtype}.")
+    return wp.from_torch(ids.to(wp.dtype_to_torch(dtype)).contiguous(), dtype=dtype)
+
+
 ##
 # Capture safety — property guard.
 ##
diff --git a/source/isaaclab/isaaclab/utils/wrench_composer.py b/source/isaaclab/isaaclab/utils/wrench_composer.py
index 6331716cad5d..ace1570dc4dc 100644
--- a/source/isaaclab/isaaclab/utils/wrench_composer.py
+++ b/source/isaaclab/isaaclab/utils/wrench_composer.py
@@ -24,6 +24,7 @@
     set_forces_to_dual_buffers_index_kernel,
     set_forces_to_dual_buffers_mask,
 )
+from .warp.utils import resolve_ids
 
 if TYPE_CHECKING:
     from ..assets import BaseArticulation, BaseRigidObject, BaseRigidObjectCollection
@@ -721,24 +722,9 @@ def _resolve_env_ids(self, env_ids: wp.array | torch.Tensor | list | slice | Non
             Environment indices.
 
         Raises:
-            TypeError: If ``env_ids`` is an unsupported type.
+            TypeError: If ``env_ids`` is a :class:`~isaaclab.utils.warp.ProxyArray`.
         """
-        if env_ids is None:
-            return self._ALL_ENV_INDICES
-        # Check tensor types before slice comparison (tensor == slice crashes)
-        if isinstance(env_ids, torch.Tensor):
-            return env_ids
-        if isinstance(env_ids, wp.array):
-            return env_ids
-        if env_ids == slice(None):
-            return self._ALL_ENV_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_ENV_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        raise TypeError(
-            f"env_ids must be None, slice(None), list, torch.Tensor, or wp.array, got {type(env_ids).__name__}"
-        )
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_ENV_INDICES, device=self.device)
 
     def _resolve_body_ids(
         self, body_ids: Sequence[int] | torch.Tensor | wp.array | slice | None
@@ -752,23 +738,9 @@ def _resolve_body_ids(
             Body indices.
 
         Raises:
-            TypeError: If ``body_ids`` is an unsupported type.
+            TypeError: If ``body_ids`` is a :class:`~isaaclab.utils.warp.ProxyArray`.
         """
-        if body_ids is None:
-            return self._ALL_BODY_INDICES
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(body_ids, torch.Tensor):
-            return body_ids
-        if isinstance(body_ids, wp.array):
-            return body_ids
-        if body_ids == slice(None):
-            return self._ALL_BODY_INDICES
-        if isinstance(body_ids, Sequence):
-            return wp.array(body_ids, dtype=wp.int32, device=self.device)
-        raise TypeError(
-            f"body_ids must be None, slice(None), a sequence, torch.Tensor, or wp.array, got {type(body_ids).__name__}"
-        )
+        return resolve_ids(ids=body_ids, all_ids=self._ALL_BODY_INDICES, device=self.device)
 
     def _ensure_composed(self):
         """Compose input buffers into output buffers if dirty."""
diff --git a/source/isaaclab/test/assets/contract/articulation_factory.py b/source/isaaclab/test/assets/contract/articulation_factory.py
index e47337eccf1c..24fd46c4e8e8 100644
--- a/source/isaaclab/test/assets/contract/articulation_factory.py
+++ b/source/isaaclab/test/assets/contract/articulation_factory.py
@@ -237,6 +237,7 @@ def _newton_articulation(N, J, B, FT, ST, device, is_fixed_base, joint_ordering,
     articulation._ALL_BODY_INDICES = indices(B, device)
     articulation._ALL_JOINT_INDICES = indices(J, device)
     articulation._ALL_ENV_MASK = wp.ones((N,), dtype=wp.bool, device=device)
+    articulation._scratch_env_mask = wp.zeros((N,), dtype=wp.bool, device=device)
     articulation._ALL_BODY_MASK = wp.ones((B,), dtype=wp.bool, device=device)
     articulation._ALL_JOINT_MASK = wp.ones((J,), dtype=wp.bool, device=device)
     articulation._resolve_and_install_ordering_maps()
diff --git a/source/isaaclab/test/assets/contract/rigid_object_factory.py b/source/isaaclab/test/assets/contract/rigid_object_factory.py
index 0bf4741ed9f5..cb108da59a1c 100644
--- a/source/isaaclab/test/assets/contract/rigid_object_factory.py
+++ b/source/isaaclab/test/assets/contract/rigid_object_factory.py
@@ -195,6 +195,7 @@ def _newton_collection(num_instances: int, num_bodies: int, device: str, monkeyp
     collection._ALL_BODY_INDICES = indices(num_bodies, device)
     collection._ALL_ENV_MASK = wp.ones((num_instances,), dtype=wp.bool, device=device)
     collection._ALL_BODY_MASK = wp.ones((num_bodies,), dtype=wp.bool, device=device)
+    collection._scratch_body_mask = wp.zeros((num_bodies,), dtype=wp.bool, device=device)
     return collection, view
 
 
diff --git a/source/isaaclab/test/assets/contract/test_articulation_contract.py b/source/isaaclab/test/assets/contract/test_articulation_contract.py
index 992792f8dbfa..3dea2cce14d2 100644
--- a/source/isaaclab/test/assets/contract/test_articulation_contract.py
+++ b/source/isaaclab/test/assets/contract/test_articulation_contract.py
@@ -139,20 +139,12 @@ def test_finders(monkeypatch, backend):
             finder("nonexistent_xyz")
 
 
-def test_resolve_ids_accept_tensor_views(monkeypatch, backend):
-    """Selector resolution honors tensor views, and environment slices alias the cached indices without copies."""
-    art, _ = _articulation(backend, "cpu", monkeypatch, num_instances=4, num_joints=4, num_bodies=4)
-    ids = torch.arange(4, dtype=torch.int32)
-    for resolve in (art._resolve_env_ids, art._resolve_joint_ids, art._resolve_body_ids):
-        assert resolve(ids).shape[0] == 4
-        assert resolve(ids[:2]).shape[0] == 2
-
-    cached = wp.to_torch(art._ALL_INDICES)
-    for selection in (slice(None), slice(1, None, 2), slice(0, 0)):
-        resolved = wp.to_torch(art._resolve_env_ids(selection))
-        torch.testing.assert_close(resolved, cached[selection])
-        assert resolved.data_ptr() == cached[selection].data_ptr()
-        assert resolved.stride() == cached[selection].stride()
+def test_resolvers_select_from_their_own_cached_indices(monkeypatch, backend):
+    """Each selector resolver returns its own cached indices for a selection of every element."""
+    art, _ = _articulation(backend, "cpu", monkeypatch)
+    assert art._resolve_env_ids(slice(None)) is art._ALL_INDICES
+    assert art._resolve_joint_ids(slice(None)) is art._ALL_JOINT_INDICES
+    assert art._resolve_body_ids(slice(None)) is art._ALL_BODY_INDICES
 
 
 # ---------------------------------------------------------------------------
@@ -526,8 +518,20 @@ def read() -> ProxyArray:
             method(**{kwarg: 1.0})
             _assert_reads_back(read(), torch.ones_like(expected), f"{writer} scalar")
 
-    if backend == "newton" and selection == "mask" and is_tendon:
-        return  # pinned by test_newton_fixed_tendon_mask_setters_reject_extra_environments
+    if writer == "set_fixed_tendon_position_limit":
+        # Limit pairs whose components are strided in memory write as contiguous ones do.
+        expected = _payload(shape, trailing, dtype, device, offset=200.0)
+        method(**{kwarg: expected.repeat_interleave(2, dim=-1)[..., ::2]})
+        _assert_reads_back(read(), expected, f"{writer} strided")
+
+    if backend == "newton" and selection == "mask" and not writer.endswith("_target"):
+        # A short mask writes only the rows it covers, even when the memory past its end selects more rows.
+        expected = read().torch.clone()
+        values = _payload(shape, trailing, dtype, device, offset=300.0)
+        method(**{kwarg: values[: N - 1], "env_mask": _mask(N, range(N), device)[: N - 1]})
+        expected[: N - 1] = values[: N - 1]
+        _assert_reads_back(read(), expected, f"{writer} short mask")
+
     extra_env = _payload((N + 1, *shape[1:]), trailing, dtype, device)
     with pytest.raises((AssertionError, RuntimeError)):
         method(**{kwarg: extra_env})
@@ -535,18 +539,6 @@ def read() -> ProxyArray:
         method(**{kwarg: wp.from_torch(extra_env.contiguous(), dtype=dtype)})
 
 
-@requires("newton")
-@pytest.mark.xfail(
-    raises=pytest.fail.Exception,
-    strict=True,
-    reason="Newton fixed-tendon mask setters slice full data without validating its shape",
-)
-def test_newton_fixed_tendon_mask_setters_reject_extra_environments(monkeypatch):
-    art, _ = _articulation("newton", "cpu", monkeypatch)
-    with pytest.raises((AssertionError, RuntimeError)):
-        art.set_fixed_tendon_stiffness_mask(stiffness=torch.ones((N + 1, FT)))
-
-
 # quantity -> (writer, keyword, trailing size). Joint partial writes are covered by the ordering contract.
 _PARTIAL_WRITES = {
     "root_pose": ("write_root_link_pose_to_sim", "root_pose", 7),
diff --git a/source/isaaclab/test/assets/contract/test_rigid_object_contract.py b/source/isaaclab/test/assets/contract/test_rigid_object_contract.py
index 1d294d9a8efc..cd800bd91696 100644
--- a/source/isaaclab/test/assets/contract/test_rigid_object_contract.py
+++ b/source/isaaclab/test/assets/contract/test_rigid_object_contract.py
@@ -97,17 +97,10 @@ def test_counts_names_finders_and_index_resolution(monkeypatch, backend, asset):
     if asset == "collection":
         with pytest.warns(DeprecationWarning):
             assert obj.find_objects(".*", as_proxy=True)[0] is proxy
-        assert obj._resolve_body_ids(torch.arange(3, dtype=torch.int32)[:2]).shape[0] == 2
 
-    # Environment selections resolve to strided views of the cached indices without copying.
-    env_ids = torch.arange(4, dtype=torch.int32)
-    assert obj._resolve_env_ids(env_ids[:2]).shape[0] == 2
-    cached = wp.to_torch(obj._ALL_INDICES if asset == "object" else obj._ALL_ENV_INDICES)
-    for selection in (slice(None), slice(1, None, 2), slice(0, 0)):
-        resolved = wp.to_torch(obj._resolve_env_ids(selection))
-        torch.testing.assert_close(resolved, cached[selection])
-        assert resolved.data_ptr() == cached[selection].data_ptr()
-        assert resolved.stride() == cached[selection].stride()
+    # Each resolver returns its own cached indices for a selection of every element.
+    assert obj._resolve_env_ids(slice(None)) is (obj._ALL_INDICES if asset == "object" else obj._ALL_ENV_INDICES)
+    assert obj._resolve_body_ids(slice(None)) is obj._ALL_BODY_INDICES
 
 
 def _expected_properties(top: str) -> dict[str, type]:
@@ -295,6 +288,30 @@ def test_writer_reads_back_full_and_partial_writes(monkeypatch, backend, device,
     expected[last] = update[last]
     torch.testing.assert_close(getattr(obj.data, getter).torch, expected, atol=1e-5, rtol=1e-5)
 
+    if (
+        asset == "collection"
+        and selection == "mask"
+        and quantity.endswith(("pose", "velocity"))
+        and backend != "ovphysx"
+    ):
+        # Collection mask writers given ``body_ids`` write only those bodies of the masked environments.
+        last_body = num_bodies - 1
+        for offset, body_ids in enumerate(
+            ([last_body], wp.array([last_body], dtype=wp.int64, device=device), slice(None, last_body - 1, -2)),
+            start=2,
+        ):
+            update = _payload(shape, trailing, offset=100.0 * offset, device=device)
+            method(**{kwarg: update}, env_mask=selectors["env_mask"], body_ids=body_ids)
+            expected[-1, -1] = update[-1, -1]
+            torch.testing.assert_close(getattr(obj.data, getter).torch, expected, atol=1e-5, rtol=1e-5)
+        if backend == "newton":
+            # A short mask writes only the rows it covers, even when the memory past its end selects more rows.
+            update = _payload(shape, trailing, offset=500.0, device=device)
+            short_mask = wp.ones(_NUM_INSTANCES, dtype=wp.bool, device=device)[: _NUM_INSTANCES - 1]
+            method(**{kwarg: update[: _NUM_INSTANCES - 1]}, env_mask=short_mask)
+            expected[: _NUM_INSTANCES - 1] = update[: _NUM_INSTANCES - 1]
+            torch.testing.assert_close(getattr(obj.data, getter).torch, expected, atol=1e-5, rtol=1e-5)
+
     # Data with an extra environment is rejected for torch and warp inputs.
     bad = _payload((_NUM_INSTANCES + 1, *shape[1:]), trailing, device=device)
     for value in (bad, wp.from_torch(bad.contiguous(), dtype=wp_dtype)):
diff --git a/source/isaaclab/test/renderers/test_simulation_render_context.py b/source/isaaclab/test/renderers/test_simulation_render_context.py
index fdcc8d4f3779..cf16bc4a2d76 100644
--- a/source/isaaclab/test/renderers/test_simulation_render_context.py
+++ b/source/isaaclab/test/renderers/test_simulation_render_context.py
@@ -317,6 +317,7 @@ def __init__(self, renderer, name, update_period=0.0):
         self._frame = ProxyArray(wp.zeros(2, dtype=wp.int64, device="cpu"))
         self._ALL_INDICES = wp.array([0, 1], dtype=wp.int32, device="cpu")
         self._ALL_ENV_MASK = wp.ones(2, dtype=wp.bool, device="cpu")
+        self._reset_mask = wp.zeros(2, dtype=wp.bool, device="cpu")
         self._create_timing_buffers()
         self._invalidate_buffers(self._ALL_ENV_MASK)
         self.pose = 0.0
diff --git a/source/isaaclab/test/sensors/test_sensor_update_schedule.py b/source/isaaclab/test/sensors/test_sensor_update_schedule.py
index 66224a3fea17..39353ecefdb3 100644
--- a/source/isaaclab/test/sensors/test_sensor_update_schedule.py
+++ b/source/isaaclab/test/sensors/test_sensor_update_schedule.py
@@ -70,6 +70,7 @@ def __init__(self, update_period: float, device: str, num_envs: int = 2):
         self._device = device
         self._num_envs = num_envs
         self._ALL_ENV_MASK = wp.ones(num_envs, dtype=wp.bool, device=device)
+        self._reset_mask = wp.zeros(num_envs, dtype=wp.bool, device=device)
         self._is_initialized = True
         self._is_visualizing = False
         self._create_timing_buffers()
diff --git a/source/isaaclab/test/utils/test_wrench_composer.py b/source/isaaclab/test/utils/test_wrench_composer.py
index 10daf0d06612..fccb5f3c8773 100644
--- a/source/isaaclab/test/utils/test_wrench_composer.py
+++ b/source/isaaclab/test/utils/test_wrench_composer.py
@@ -474,11 +474,9 @@ def test_deprecated_writers_warn_and_keep_add_and_set_behavior() -> None:
     _assert_vectors(composer.out_torque_b, torch.zeros((2, 2, 3)))
 
 
-def test_invalid_selection_and_empty_wrench_input_are_reported() -> None:
+def test_empty_wrench_input_is_reported() -> None:
     composer = _make_composer()
 
-    with pytest.raises(TypeError, match="env_ids must be"):
-        composer.add_forces_and_torques_index(forces=_vectors(torch.ones((1, 2, 3))), env_ids=(0,))
     for method in ("add_forces_and_torques_index", "set_forces_and_torques_mask"):
         with pytest.warns(UserWarning, match="No forces or torques"):
             getattr(composer, method)()
diff --git a/source/isaaclab/test/utils/warp/test_resolve_selection.py b/source/isaaclab/test/utils/warp/test_resolve_selection.py
new file mode 100644
index 000000000000..610b90cf72d0
--- /dev/null
+++ b/source/isaaclab/test/utils/warp/test_resolve_selection.py
@@ -0,0 +1,161 @@
+# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Tests for resolving index selections with :func:`resolve_ids` and :func:`resolve_1d_mask`."""
+
+import pytest
+import torch
+import warp as wp
+
+from isaaclab.test.utils import DeviceScope, test_devices
+from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids
+
+
+def _all_ids(n: int, device: str) -> wp.array:
+    return wp.array(list(range(n)), dtype=wp.int32, device=device)
+
+
+@pytest.mark.parametrize("device", test_devices())
+@pytest.mark.parametrize("dtype", [None, wp.int32])
+def test_resolve_ids(device, dtype):
+    """Every selection resolves to device ids; a selection of every element is the shared constant itself.
+
+    Without ``dtype``, tensors and Warp arrays pass through and positive-step slices view the shared ids without a
+    copy. ``dtype=wp.int32`` gives a contiguous one-dimensional int32 Warp array for every kind of ids.
+    """
+    all_ids = _all_ids(10, device)
+    torch_device = wp.device_to_torch(device)
+    ids_int32 = wp.array([5], dtype=wp.int32, device=device)
+    for ids in (None, slice(None)):
+        assert resolve_ids(ids=ids, all_ids=all_ids, device=device, dtype=dtype) is all_ids
+    assert resolve_ids(ids=ids_int32, all_ids=all_ids, device=device, dtype=dtype) is ids_int32
+    for ids, expected in (
+        ([3, 8], [3, 8]),
+        (slice(2, 8, 3), [2, 5]),
+        (slice(None, None, -4), [9, 5, 1]),
+        (torch.tensor([4, 2], dtype=torch.int64, device=torch_device), [4, 2]),
+        (torch.arange(10, device=torch_device)[::3], [0, 3, 6, 9]),
+        (wp.array([7, 1], dtype=wp.int64, device=device), [7, 1]),
+    ):
+        resolved = resolve_ids(ids=ids, all_ids=all_ids, device=device, dtype=dtype)
+        if dtype is None:
+            assert resolved is ids or isinstance(ids, (list, slice))
+        else:
+            assert isinstance(resolved, wp.array) and resolved.dtype == dtype and resolved.is_contiguous
+        assert (wp.to_torch(resolved) if isinstance(resolved, wp.array) else resolved).tolist() == expected
+    with pytest.raises(TypeError, match="ProxyArray"):
+        resolve_ids(ids=ProxyArray(ids_int32), all_ids=all_ids, device=device, dtype=dtype)
+    if dtype is None:
+        cached = wp.to_torch(all_ids)
+        for selection in (slice(1, None, 2), slice(0, 0)):
+            resolved = wp.to_torch(resolve_ids(ids=selection, all_ids=all_ids, device=device))
+            assert resolved.data_ptr() == cached[selection].data_ptr()
+            assert resolved.stride() == cached[selection].stride()
+    else:
+        for ids, error in (
+            (torch.tensor([1.0], device=torch_device), TypeError),
+            (wp.array([1.0], dtype=wp.float32, device=device), TypeError),
+            (torch.zeros((2, 2), dtype=torch.int64, device=torch_device), ValueError),
+        ):
+            with pytest.raises(error):
+                resolve_ids(ids=ids, all_ids=all_ids, device=device, dtype=dtype)
+
+
+@pytest.mark.parametrize("device", test_devices())
+@pytest.mark.parametrize("mask_type", ["warp", "torch"])
+def test_resolve_ids_from_a_mask(device, mask_type):
+    """A mask resolves to its ascending ids, takes precedence over ids, and honours ``dtype``."""
+    mask_bool = torch.tensor([0, 1, 1, 0, 1, 0, 0, 1], dtype=torch.bool, device=wp.device_to_torch(device))
+    mask = wp.from_torch(mask_bool, dtype=wp.bool) if mask_type == "warp" else mask_bool
+    all_ids = _all_ids(mask_bool.shape[0], device)
+    ids = resolve_ids(ids=[0, 1], mask=mask, all_ids=all_ids, device=device)
+    assert ids.dtype == torch.int64 and ids.tolist() == [1, 2, 4, 7]
+    ids_int32 = resolve_ids(mask=mask, all_ids=all_ids, device=device, dtype=wp.int32)
+    assert isinstance(ids_int32, wp.array) and ids_int32.dtype == wp.int32 and ids_int32.is_contiguous
+    assert ids_int32.numpy().tolist() == [1, 2, 4, 7]
+
+
+@pytest.mark.parametrize("device", test_devices())
+@pytest.mark.parametrize(
+    "ids_type", ["list", "slice", "reverse_slice", "torch_int64", "torch_int32", "warp_int32", "warp_int64"]
+)
+def test_resolve_1d_mask_from_ids(device, ids_type):
+    """Ids of every type are written into the scratch mask, which is cleared first."""
+    n = 12
+    all_mask = wp.ones(n, dtype=wp.bool, device=device)
+    scratch = wp.ones(n, dtype=wp.bool, device=device)
+    selected = [1, 4, 5, 11]
+    torch_device = wp.device_to_torch(device)
+    ids = {
+        "list": selected,
+        "slice": slice(1, 12, 3),
+        "reverse_slice": slice(None, None, -2),
+        "torch_int64": torch.tensor(selected, dtype=torch.int64, device=torch_device),
+        "torch_int32": torch.tensor(selected, dtype=torch.int32, device=torch_device),
+        "warp_int32": wp.array(selected, dtype=wp.int32, device=device),
+        "warp_int64": wp.array(selected, dtype=wp.int64, device=device),
+    }[ids_type]
+    expected = [False] * n
+    for i in range(n)[ids] if isinstance(ids, slice) else selected:
+        expected[i] = True
+    mask = resolve_1d_mask(ids=ids, all_mask=all_mask, scratch_mask=scratch, device=device)
+    assert mask is scratch
+    assert mask.numpy().tolist() == expected
+
+
+@pytest.mark.parametrize("device", test_devices())
+def test_resolve_1d_mask_needs_a_scratch_mask_only_for_ids(device):
+    """A mask or no selection resolves without a scratch mask; ids without one raise."""
+    all_mask = wp.ones(5, dtype=wp.bool, device=device)
+    mask = wp.array([True, False, True, False, False], dtype=wp.bool, device=device)
+    assert resolve_1d_mask(ids=[0], mask=mask, all_mask=all_mask, device=device) is mask
+    assert resolve_1d_mask(all_mask=all_mask, device=device) is all_mask
+    assert resolve_1d_mask(ids=slice(None), all_mask=all_mask, device=device) is all_mask
+    mask_torch = torch.tensor([False, True, True, False, False], device=wp.device_to_torch(device))
+    resolved = resolve_1d_mask(mask=mask_torch, all_mask=all_mask, device=device)
+    assert resolved.dtype == wp.bool and resolved.numpy().tolist() == [False, True, True, False, False]
+    with pytest.raises(ValueError, match="scratch_mask"):
+        resolve_1d_mask(ids=[1], all_mask=all_mask, device=device)
+
+
+@pytest.mark.parametrize("device", test_devices(DeviceScope.CUDA))
+def test_resolve_1d_mask_copies_a_selection_on_another_device(device, monkeypatch):
+    """A Warp mask or Warp ids on another device are copied to ``device``.
+
+    The strict launch mode rejects a kernel argument on another device, which the default mode may read through
+    host-memory addressing or fault on.
+    """
+    monkeypatch.setattr(wp.config, "launch_array_access_mode", wp.config.LaunchArrayAccessMode.STRICT)
+    all_mask = wp.ones(3, dtype=wp.bool, device=device)
+    scratch = wp.zeros(3, dtype=wp.bool, device=device)
+    mask = wp.array([True, False, True], dtype=wp.bool, device="cpu")
+    resolved = resolve_1d_mask(mask=mask, all_mask=all_mask, device=device)
+    assert str(resolved.device) == device and resolved.numpy().tolist() == [True, False, True]
+    ids = wp.array([0, 2], dtype=wp.int32, device="cpu")
+    assert resolve_1d_mask(ids=ids, all_mask=all_mask, scratch_mask=scratch, device=device) is scratch
+    assert scratch.numpy().tolist() == [True, False, True]
+
+
+@pytest.mark.parametrize("device", test_devices(DeviceScope.CUDA))
+def test_resolve_1d_mask_in_a_graph_capture(device):
+    """Inside a capture, a boolean mask on device resolves; ids or a mask that needs a cast or copy raise.
+
+    ``"cuda"`` names the current CUDA device, so a mask on it needs no copy.
+    """
+    all_mask = wp.ones(3, dtype=wp.bool, device=device)
+    scratch = wp.zeros(3, dtype=wp.bool, device=device)
+    mask_wp = wp.array([True, False, True], dtype=wp.bool, device=device)
+    mask_torch = torch.tensor([False, True, True], device=device)
+    mask_int = mask_torch.int()
+    mask_cpu = wp.array([True, False, True], dtype=wp.bool, device="cpu")
+    with wp.ScopedDevice(device), wp.ScopedCapture():
+        assert resolve_1d_mask(mask=mask_wp, all_mask=all_mask, device=device) is mask_wp
+        resolved = resolve_1d_mask(mask=mask_torch, all_mask=all_mask, device=device)
+        assert resolve_1d_mask(mask=mask_torch, all_mask=all_mask, device="cuda").ptr == resolved.ptr
+        for selection in ({"mask": mask_int}, {"mask": mask_cpu}, {"ids": [0]}):
+            with pytest.raises(RuntimeError, match="capturable"):
+                resolve_1d_mask(**selection, all_mask=all_mask, scratch_mask=scratch, device=device)
+    assert resolved.numpy().tolist() == [False, True, True]
diff --git a/source/isaaclab/test/utils/warp/test_write_with_mask.py b/source/isaaclab/test/utils/warp/test_write_with_mask.py
new file mode 100644
index 000000000000..7909f05676f3
--- /dev/null
+++ b/source/isaaclab/test/utils/warp/test_write_with_mask.py
@@ -0,0 +1,38 @@
+# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Tests for writing through masks with :func:`write_2d_with_mask`."""
+
+import pytest
+import torch
+import warp as wp
+
+from isaaclab.test.utils import test_devices
+from isaaclab.utils.warp.utils import write_2d_with_mask
+
+
+@pytest.mark.parametrize("device", test_devices())
+@pytest.mark.parametrize("data_type", ["scalar", "torch", "warp", "torch_strided_vec2f"])
+def test_write_2d_with_mask(device, data_type):
+    """Only entries selected by both masks are written, and a short mask writes only the rows it covers.
+
+    The environment mask and the data are views whose memory continues with a selected third row, so a launch over the
+    full output would write that row too.
+    """
+    torch_device = wp.device_to_torch(device)
+    env_mask = wp.array([True, False, True], dtype=wp.bool, device=device)[:2]
+    item_mask = wp.array([False, True], dtype=wp.bool, device=device)
+    if data_type == "torch_strided_vec2f":
+        values = torch.arange(1, 13, dtype=torch.float32, device=torch_device).reshape(3, 2, 2)
+        data = values.repeat_interleave(2, dim=-1)[..., ::2][:2]
+        out = wp.zeros((3, 2), dtype=wp.vec2f, device=device)
+    else:
+        values = torch.arange(1, 7, dtype=torch.float32, device=torch_device).reshape(3, 2)
+        data = {"scalar": 7.0, "torch": values[:2], "warp": wp.from_torch(values)[:2]}[data_type]
+        out = wp.zeros((3, 2), dtype=wp.float32, device=device)
+    write_2d_with_mask(data, env_mask, item_mask, out, device)
+    expected = torch.zeros_like(values)
+    expected[0, 1] = 7.0 if data_type == "scalar" else values[0, 1]
+    assert torch.equal(wp.to_torch(out), expected)
diff --git a/source/isaaclab_experimental/changelog.d/jichuanh-id-mask.changed.rst b/source/isaaclab_experimental/changelog.d/jichuanh-id-mask.changed.rst
new file mode 100644
index 000000000000..ce57c9e7851f
--- /dev/null
+++ b/source/isaaclab_experimental/changelog.d/jichuanh-id-mask.changed.rst
@@ -0,0 +1,2 @@
+* Changed ``isaaclab_experimental.utils.warp.resolve_1d_mask`` to be
+  :func:`isaaclab.utils.warp.utils.resolve_1d_mask` instead of a copy of it.
diff --git a/source/isaaclab_experimental/isaaclab_experimental/utils/warp/__init__.py b/source/isaaclab_experimental/isaaclab_experimental/utils/warp/__init__.py
index 2d071b823a46..757a45e8b825 100644
--- a/source/isaaclab_experimental/isaaclab_experimental/utils/warp/__init__.py
+++ b/source/isaaclab_experimental/isaaclab_experimental/utils/warp/__init__.py
@@ -5,11 +5,12 @@
 
 """Warp utility functions and shared kernels for isaaclab_experimental."""
 
+from isaaclab.utils.warp.utils import resolve_1d_mask
+
 from .kernels import compute_reset_scale, count_masked
 from .utils import (
     WarpCapturable,
     is_warp_capturable,
-    resolve_1d_mask,
     warp_capturable,
     wrap_to_pi,
     zero_masked_2d,
diff --git a/source/isaaclab_experimental/isaaclab_experimental/utils/warp/utils.py b/source/isaaclab_experimental/isaaclab_experimental/utils/warp/utils.py
index a90f6b2d6fc6..6b8aafc415f8 100644
--- a/source/isaaclab_experimental/isaaclab_experimental/utils/warp/utils.py
+++ b/source/isaaclab_experimental/isaaclab_experimental/utils/warp/utils.py
@@ -5,97 +5,9 @@
 
 from __future__ import annotations
 
-from collections.abc import Sequence
-
-import torch
 import warp as wp
 
 
-@wp.kernel
-def _set_mask_from_ids(
-    mask: wp.array(dtype=wp.bool),
-    ids: wp.array(dtype=wp.int32),
-):
-    """Set ``mask[ids[i]] = True`` for each thread *i*."""
-    i = wp.tid()
-    mask[ids[i]] = True
-
-
-def resolve_1d_mask(
-    *,
-    ids: Sequence[int] | slice | wp.array | torch.Tensor | None,
-    mask: wp.array | torch.Tensor | None,
-    all_mask: wp.array,
-    scratch_mask: wp.array,
-    device: str,
-) -> wp.array:
-    """Resolve ids/mask into a warp boolean mask.
-
-    Matches the contract of ``ArticulationData._resolve_1d_mask`` on dev/newton.
-    Callers must provide pre-allocated ``all_mask`` (all-True) and ``scratch_mask``
-    (reusable working buffer). No allocations happen inside this function.
-
-    Args:
-        ids: Indices to set to ``True``. ``None`` or ``slice(None)`` means all.
-        mask: Explicit boolean mask. If provided, returned directly (after
-            torch->warp normalization if needed). Takes precedence over *ids*.
-        all_mask: Pre-allocated all-True mask of shape ``(size,)``, returned
-            when both *ids* and *mask* are ``None``.
-        scratch_mask: Pre-allocated scratch mask of shape ``(size,)``, filled
-            in-place when *ids* are provided.
-        device: Warp device string.
-
-    Returns:
-        A ``wp.array(dtype=wp.bool)`` -- ``mask``, ``all_mask``, or ``scratch_mask``.
-    """
-    # Fast path: explicit mask provided.
-    if mask is not None:
-        if isinstance(mask, torch.Tensor):
-            if mask.dtype != torch.bool:
-                mask = mask.to(dtype=torch.bool)
-            if str(mask.device) != device:
-                mask = mask.to(device)
-            return wp.from_torch(mask, dtype=wp.bool)
-        return mask
-
-    # Fast path: all ids.
-    if ids is None or (isinstance(ids, slice) and ids == slice(None)):
-        return all_mask
-
-    # Normalize slice into explicit indices.
-    if isinstance(ids, slice):
-        start, stop, step = ids.indices(scratch_mask.shape[0])
-        ids = list(range(start, stop, step))
-    elif not isinstance(ids, (torch.Tensor, wp.array)):
-        ids = list(ids)
-
-    # Prepare output mask.
-    scratch_mask.fill_(False)
-
-    # Normalize ids to wp.int32 array and launch kernel.
-    if isinstance(ids, torch.Tensor):
-        if ids.numel() == 0:
-            return scratch_mask
-        if str(ids.device) != device:
-            ids = ids.to(device)
-        if ids.dtype != torch.int32:
-            ids = ids.to(dtype=torch.int32)
-        if not ids.is_contiguous():
-            ids = ids.contiguous()
-        ids_wp = wp.from_torch(ids, dtype=wp.int32)
-    elif isinstance(ids, wp.array):
-        if ids.shape[0] == 0:
-            return scratch_mask
-        ids_wp = ids
-    else:
-        if len(ids) == 0:
-            return scratch_mask
-        ids_wp = wp.array(ids, dtype=wp.int32, device=device)
-
-    wp.launch(kernel=_set_mask_from_ids, dim=ids_wp.shape[0], inputs=[scratch_mask, ids_wp], device=device)
-    return scratch_mask
-
-
 def warp_capturable(capturable: bool):
     """Annotate an MDP term's CUDA-graph capturability.
 
diff --git a/source/isaaclab_newton/changelog.d/jichuanh-id-mask.changed.rst b/source/isaaclab_newton/changelog.d/jichuanh-id-mask.changed.rst
new file mode 100644
index 000000000000..e0e59800bd6d
--- /dev/null
+++ b/source/isaaclab_newton/changelog.d/jichuanh-id-mask.changed.rst
@@ -0,0 +1,14 @@
+* Changed the env selection helpers of the Newton assets to resolve ``env_ids`` through
+  :func:`~isaaclab.utils.warp.utils.resolve_ids` and ``env_mask`` through
+  :func:`~isaaclab.utils.warp.utils.resolve_1d_mask`. Any integer sequence and slices with a negative step are accepted,
+  ids on another device are moved to the asset's device, and a :class:`~isaaclab.utils.warp.ProxyArray` is rejected
+  with a :class:`TypeError`.
+* Changed the body, joint and tendon selection helpers of the Newton assets to resolve ids and masks through
+  :func:`~isaaclab.utils.warp.utils.resolve_ids`, as the env selection does, so slices other than ``slice(None)`` are
+  accepted.
+* Changed the joint-coordinate writes of :class:`~isaaclab_newton.assets.Articulation` to write env ids into a
+  scratch mask of the articulation instead of allocating a mask on every call.
+* Changed the mask writers of :class:`~isaaclab_newton.assets.RigidObjectCollection` and the fixed-tendon mask setters
+  of :class:`~isaaclab_newton.assets.Articulation` to write through the masks, as the other Newton mask writers do,
+  instead of converting the masks to indices, which synchronized the host with the GPU on every call. Recorded into
+  a CUDA graph, ``write_fixed_tendon_properties_to_sim_mask`` refreshes the solver's tendon properties on every replay.
diff --git a/source/isaaclab_newton/changelog.d/jichuanh-id-mask.fixed.rst b/source/isaaclab_newton/changelog.d/jichuanh-id-mask.fixed.rst
new file mode 100644
index 000000000000..638c02730a49
--- /dev/null
+++ b/source/isaaclab_newton/changelog.d/jichuanh-id-mask.fixed.rst
@@ -0,0 +1,2 @@
+* Fixed the fixed-tendon mask setters of :class:`~isaaclab_newton.assets.Articulation` accepting data whose shape
+  does not match the articulation.
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/articulation/articulation.py b/source/isaaclab_newton/isaaclab_newton/assets/articulation/articulation.py
index 047640bb9ab3..5f88d6b82bb4 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/articulation/articulation.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/articulation/articulation.py
@@ -12,7 +12,7 @@
 import re
 import warnings
 from collections.abc import Sequence
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING
 
 import numpy as np
 import torch
@@ -33,6 +33,7 @@
 from isaaclab.utils.string import resolve_matching_names, resolve_matching_names_values
 from isaaclab.utils.version import get_isaac_sim_version, has_kit
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids, write_2d_with_mask
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_newton.assets import kernels as shared_kernels
@@ -2296,15 +2297,11 @@ def write_joint_viscous_friction_coefficient_to_sim_mask(
     Operations - Newton Actuator Parameter Writers.
     """
 
-    @staticmethod
-    @wp.kernel(enable_backward=False)
-    def _build_env_mask_kernel(mask: wp.array(dtype=wp.bool), indices: wp.array(dtype=Any)):
-        i = wp.tid()
-        mask[wp.int32(indices[i])] = True
-
     def _env_ids_to_mask(self, env_ids: wp.array | torch.Tensor) -> wp.array:
         """Convert env_ids to a boolean Warp mask.
 
+        Needed because :func:`scatter_joint_coordinates` only takes a mask.
+
         Args:
             env_ids: Environment indices as returned by :meth:`_resolve_env_ids`, which may be a
                 warp array or a torch tensor of any integer width.
@@ -2314,11 +2311,9 @@ def _env_ids_to_mask(self, env_ids: wp.array | torch.Tensor) -> wp.array:
         """
         if env_ids is self._ALL_INDICES:
             return self._ALL_ENV_MASK
-        if isinstance(env_ids, torch.Tensor):
-            env_ids = wp.from_torch(env_ids)
-        mask = wp.zeros(self.num_instances, dtype=wp.bool, device=self.device)
-        wp.launch(self._build_env_mask_kernel, dim=env_ids.shape[0], inputs=[mask, env_ids], device=self.device)
-        return mask
+        return resolve_1d_mask(
+            ids=env_ids, all_mask=self._ALL_ENV_MASK, scratch_mask=self._scratch_env_mask, device=self.device
+        )
 
     """
     Operations - Setters.
@@ -2705,8 +2700,8 @@ def set_fixed_tendon_stiffness_mask(
             This method expects full data.
 
         .. tip::
-            For maximum performance we recommend using the index method. This is because in PhysX, the tensor API
-            is only supporting indexing, hence masks need to be converted to indices.
+            Both the index and mask methods have dedicated optimized implementations. Performance is similar for both.
+            However, to allow graphed pipelines, the mask method must be used.
 
         Args:
             stiffness: Fixed tendon stiffness. Shape is (num_instances, num_fixed_tendons).
@@ -2714,13 +2709,10 @@ def set_fixed_tendon_stiffness_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
-        self.set_fixed_tendon_stiffness_index(
-            stiffness=self._select_full_data(stiffness, env_ids, fixed_tendon_ids),
-            fixed_tendon_ids=fixed_tendon_ids,
-            env_ids=env_ids,
-        )
+        env_mask = self._resolve_mask(env_mask, self._ALL_ENV_MASK)
+        fixed_tendon_mask = self._resolve_mask(fixed_tendon_mask, self._ALL_FIXED_TENDON_MASK)
+        self.assert_shape_and_dtype_mask(stiffness, (env_mask, fixed_tendon_mask), wp.float32, "stiffness")
+        write_2d_with_mask(stiffness, env_mask, fixed_tendon_mask, self.data._fixed_tendon_stiffness, self.device)
 
     def set_fixed_tendon_damping_index(
         self,
@@ -2802,8 +2794,8 @@ def set_fixed_tendon_damping_mask(
             This method expects full data.
 
         .. tip::
-            For maximum performance we recommend using the index method. This is because in PhysX, the tensor API
-            is only supporting indexing, hence masks need to be converted to indices.
+            Both the index and mask methods have dedicated optimized implementations. Performance is similar for both.
+            However, to allow graphed pipelines, the mask method must be used.
 
         Args:
             damping: Fixed tendon damping. Shape is (num_instances, num_fixed_tendons).
@@ -2811,13 +2803,10 @@ def set_fixed_tendon_damping_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
-        self.set_fixed_tendon_damping_index(
-            damping=self._select_full_data(damping, env_ids, fixed_tendon_ids),
-            fixed_tendon_ids=fixed_tendon_ids,
-            env_ids=env_ids,
-        )
+        env_mask = self._resolve_mask(env_mask, self._ALL_ENV_MASK)
+        fixed_tendon_mask = self._resolve_mask(fixed_tendon_mask, self._ALL_FIXED_TENDON_MASK)
+        self.assert_shape_and_dtype_mask(damping, (env_mask, fixed_tendon_mask), wp.float32, "damping")
+        write_2d_with_mask(damping, env_mask, fixed_tendon_mask, self.data._fixed_tendon_damping, self.device)
 
     def set_fixed_tendon_limit_stiffness_index(
         self,
@@ -2919,8 +2908,8 @@ def set_fixed_tendon_position_limit_mask(
             This method expects full data.
 
         .. tip::
-            For maximum performance we recommend using the index method. This is because in PhysX, the tensor API
-            is only supporting indexing, hence masks need to be converted to indices.
+            Both the index and mask methods have dedicated optimized implementations. Performance is similar for both.
+            However, to allow graphed pipelines, the mask method must be used.
 
         Args:
             limit: Fixed tendon position limits ``[lower, upper]`` [m]. Shape is (num_instances, num_fixed_tendons)
@@ -2928,13 +2917,12 @@ def set_fixed_tendon_position_limit_mask(
             fixed_tendon_mask: Fixed tendon mask. If None, then all fixed tendons are used.
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
-        self.set_fixed_tendon_position_limit_index(
-            limit=self._select_full_data(limit, env_ids, fixed_tendon_ids),
-            fixed_tendon_ids=fixed_tendon_ids,
-            env_ids=env_ids,
-        )
+        env_mask = self._resolve_mask(env_mask, self._ALL_ENV_MASK)
+        fixed_tendon_mask = self._resolve_mask(fixed_tendon_mask, self._ALL_FIXED_TENDON_MASK)
+        self.assert_shape_and_dtype_mask(limit, (env_mask, fixed_tendon_mask), wp.vec2f, "limit")
+        if isinstance(limit, float):
+            raise ValueError("Fixed tendon position limits must be a tensor or array, not a float.")
+        write_2d_with_mask(limit, env_mask, fixed_tendon_mask, self.data._fixed_tendon_pos_limits, self.device)
 
     def set_fixed_tendon_rest_length_index(
         self,
@@ -3134,10 +3122,31 @@ def write_fixed_tendon_properties_to_sim_mask(
             fixed_tendon_mask: Fixed tendon mask. If None, then all fixed tendons are updated.
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
-        self.write_fixed_tendon_properties_to_sim_index(
-            fixed_tendon_ids=self._resolve_fixed_tendon_mask(fixed_tendon_mask),
-            env_ids=self._resolve_env_mask(env_mask),
+        env_mask = self._resolve_mask(env_mask, self._ALL_ENV_MASK)
+        fixed_tendon_mask = self._resolve_mask(fixed_tendon_mask, self._ALL_FIXED_TENDON_MASK)
+        wp.launch(
+            articulation_kernels.copy_fixed_tendon_properties_with_mask,
+            dim=(env_mask.shape[0], fixed_tendon_mask.shape[0]),
+            inputs=[
+                env_mask,
+                fixed_tendon_mask,
+                self.data._fixed_tendon_stiffness,
+                self.data._fixed_tendon_damping,
+                self.data._fixed_tendon_pos_limits,
+            ],
+            outputs=[
+                self.data._sim_bind_fixed_tendon_stiffness,
+                self.data._sim_bind_fixed_tendon_damping,
+                self.data._sim_bind_fixed_tendon_pos_limits,
+            ],
+            device=self.device,
         )
+        # the solver keeps its own copy of the tendon properties and only re-reads them when notified;
+        # a capture records the refresh, so every replay reaches the solver
+        if wp.get_device(self.device).is_capturing:
+            self._backend_manager.backend.solver.notify_model_changed(ModelFlags.TENDON_PROPERTIES)
+        else:
+            self._backend_manager.add_model_change(ModelFlags.TENDON_PROPERTIES)
 
     def set_spatial_tendon_stiffness_index(
         self,
@@ -3443,6 +3452,7 @@ def _clear_callbacks(self) -> None:
     def _create_buffers(self):
         self._ALL_INDICES = wp.array(np.arange(self.num_instances, dtype=np.int32), device=self.device)
         self._ALL_ENV_MASK = wp.ones((self.num_instances,), dtype=wp.bool, device=self.device)
+        self._scratch_env_mask = wp.zeros((self.num_instances,), dtype=wp.bool, device=self.device)
         self._ALL_JOINT_INDICES = wp.array(np.arange(self.num_joints, dtype=np.int32), device=self.device)
         self._ALL_JOINT_MASK = wp.ones((self.num_joints,), dtype=wp.bool, device=self.device)
         self._ALL_BODY_INDICES = wp.array(np.arange(self.num_bodies, dtype=np.int32), device=self.device)
@@ -3718,15 +3728,7 @@ def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array | No
         Returns:
             Environment indices.
         """
-        if isinstance(env_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if (env_ids is None) or (env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self.device)
 
     def _resolve_joint_ids(self, joint_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
         """Resolve joint indices to a warp array or tensor.
@@ -3737,13 +3739,7 @@ def _resolve_joint_ids(self, joint_ids: Sequence[int] | torch.Tensor | wp.array
         Returns:
             A warp array of joint indices or a tensor of joint indices.
         """
-        if isinstance(joint_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(joint_ids, list):
-            return wp.array(joint_ids, dtype=wp.int32, device=self.device)
-        if (joint_ids is None) or (joint_ids == slice(None)):
-            return self._ALL_JOINT_INDICES
-        return joint_ids
+        return resolve_ids(ids=joint_ids, all_ids=self._ALL_JOINT_INDICES, device=self.device)
 
     def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
         """Resolve body indices to a warp array or tensor.
@@ -3754,13 +3750,7 @@ def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array |
         Returns:
             A warp array of body indices or a tensor of body indices.
         """
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self.device)
-        if (body_ids is None) or (body_ids == slice(None)):
-            return self._ALL_BODY_INDICES
-        return body_ids
+        return resolve_ids(ids=body_ids, all_ids=self._ALL_BODY_INDICES, device=self.device)
 
     def _resolve_fixed_tendon_ids(
         self, tendon_ids: Sequence[int] | torch.Tensor | wp.array | None
@@ -3773,13 +3763,7 @@ def _resolve_fixed_tendon_ids(
         Returns:
             A warp array of tendon indices or a tensor of tendon indices.
         """
-        if isinstance(tendon_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(tendon_ids, list):
-            return wp.array(tendon_ids, dtype=wp.int32, device=self.device)
-        if (tendon_ids is None) or (tendon_ids == slice(None)):
-            return self._ALL_FIXED_TENDON_INDICES
-        return tendon_ids
+        return resolve_ids(ids=tendon_ids, all_ids=self._ALL_FIXED_TENDON_INDICES, device=self.device)
 
     def _resolve_spatial_tendon_ids(
         self, spatial_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None
@@ -3792,27 +3776,7 @@ def _resolve_spatial_tendon_ids(
         Returns:
             A warp array of spatial tendon indices or a tensor of spatial tendon indices.
         """
-        if isinstance(spatial_tendon_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(spatial_tendon_ids, list):
-            return wp.array(spatial_tendon_ids, dtype=wp.int32, device=self.device)
-        if (spatial_tendon_ids is None) or (spatial_tendon_ids == slice(None)):
-            return self._ALL_SPATIAL_TENDON_INDICES
-        return spatial_tendon_ids
-
-    def _resolve_env_mask(self, env_mask: wp.array | torch.Tensor | None) -> wp.array | torch.Tensor:
-        """Resolve an environment mask to environment indices."""
-        return self._ALL_INDICES if env_mask is None else self._mask_to_ids(env_mask)
-
-    def _resolve_fixed_tendon_mask(self, fixed_tendon_mask: wp.array | torch.Tensor | None) -> wp.array | torch.Tensor:
-        """Resolve a fixed tendon mask to fixed tendon indices."""
-        return self._ALL_FIXED_TENDON_INDICES if fixed_tendon_mask is None else self._mask_to_ids(fixed_tendon_mask)
-
-    @staticmethod
-    def _mask_to_ids(mask: wp.array | torch.Tensor) -> torch.Tensor:
-        """Convert a boolean mask to int32 indices."""
-        mask = wp.to_torch(mask) if isinstance(mask, wp.array) else mask
-        return torch.nonzero(mask)[:, 0].to(torch.int32)
+        return resolve_ids(ids=spatial_tendon_ids, all_ids=self._ALL_SPATIAL_TENDON_INDICES, device=self.device)
 
     @staticmethod
     def _to_torch_ids(ids: wp.array | torch.Tensor) -> torch.Tensor:
@@ -3837,12 +3801,7 @@ def _resolve_mask(self, mask: wp.array | torch.Tensor | None, full_mask: wp.arra
         Returns:
             A warp array of mask.
         """
-        if mask is None:
-            return full_mask
-
-        if isinstance(mask, torch.Tensor):
-            return wp.from_torch(mask, dtype=wp.bool)
-        return mask
+        return resolve_1d_mask(mask=mask, all_mask=full_mask, device=self.device)
 
     """
     Deprecated methods.
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/articulation/kernels.py b/source/isaaclab_newton/isaaclab_newton/assets/articulation/kernels.py
index 60544e3a4100..7ad2bd59f057 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/articulation/kernels.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/articulation/kernels.py
@@ -553,6 +553,36 @@ def float_data_to_buffer_with_indices_kernel(
     return _FLOAT_DATA_TO_BUFFER_WITH_INDICES_DISPATCHER.select(env_ids, joint_ids)
 
 
+@wp.kernel
+def copy_fixed_tendon_properties_with_mask(
+    env_mask: wp.array(dtype=wp.bool),
+    tendon_mask: wp.array(dtype=wp.bool),
+    stiffness: wp.array2d(dtype=wp.float32),
+    damping: wp.array2d(dtype=wp.float32),
+    pos_limits: wp.array2d(dtype=wp.vec2f),
+    sim_stiffness: wp.array2d(dtype=wp.float32),
+    sim_damping: wp.array2d(dtype=wp.float32),
+    sim_pos_limits: wp.array2d(dtype=wp.vec2f),
+):
+    """Copy the staged fixed-tendon stiffness, damping and position limits to the simulation where both masks are true.
+
+    Args:
+        env_mask: Environment mask. Shape is (num_instances,).
+        tendon_mask: Fixed-tendon mask. Shape is (num_fixed_tendons,).
+        stiffness: Staged stiffness. Shape is (num_instances, num_fixed_tendons).
+        damping: Staged damping. Shape is (num_instances, num_fixed_tendons).
+        pos_limits: Staged position limits. Shape is (num_instances, num_fixed_tendons).
+        sim_stiffness: Simulation stiffness. Shape is (num_instances, num_fixed_tendons).
+        sim_damping: Simulation damping. Shape is (num_instances, num_fixed_tendons).
+        sim_pos_limits: Simulation position limits. Shape is (num_instances, num_fixed_tendons).
+    """
+    i, j = wp.tid()
+    if env_mask[i] and tendon_mask[j]:
+        sim_stiffness[i, j] = stiffness[i, j]
+        sim_damping[i, j] = damping[i, j]
+        sim_pos_limits[i, j] = pos_limits[i, j]
+
+
 @wp.kernel
 def float_data_to_buffer_with_mask(
     in_data: wp.float32,
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/cable_object/cable_object.py b/source/isaaclab_newton/isaaclab_newton/assets/cable_object/cable_object.py
index 2bc5ab64aaa5..15d6ea42f989 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/cable_object/cable_object.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/cable_object/cable_object.py
@@ -18,6 +18,7 @@
 from isaaclab.assets.cable_object.base_cable_object import BaseCableObject
 from isaaclab.sim.utils.queries import has_deformable_curve_api, path_expr_to_glob, resolve_matching_prims_from_source
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_ids
 
 from .cable_object_data import CableObjectData
 from .kernels import (
@@ -207,15 +208,7 @@ def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array(dtyp
         dtype=wp.int32
     ):
         """Resolve environment indices to a Warp array."""
-        if env_ids is None or (isinstance(env_ids, slice) and env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, torch.Tensor):
-            return wp.from_torch(env_ids.to(device=self.device, dtype=torch.int32).contiguous(), dtype=wp.int32)
-        if isinstance(env_ids, Sequence):
-            return wp.array(list(env_ids), dtype=wp.int32, device=self.device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self.device, dtype=wp.int32)
 
     def _write_segment_state_to_sim(
         self,
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/deformable_object/deformable_object.py b/source/isaaclab_newton/isaaclab_newton/assets/deformable_object/deformable_object.py
index 40d15f7461aa..e90a1a98776c 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/deformable_object/deformable_object.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/deformable_object/deformable_object.py
@@ -17,6 +17,7 @@
 from isaaclab.assets.deformable_object.base_deformable_object import BaseDeformableObject
 from isaaclab.markers import VisualizationMarkers
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids
 
 from .deformable_object_data import DeformableObjectData
 from .kernels import (
@@ -402,23 +403,11 @@ def write_nodal_kinematic_target_to_sim_mask(
 
     def _resolve_env_ids(self, env_ids):
         """Resolve environment indices to a warp int32 array."""
-        if env_ids is None or (isinstance(env_ids, slice) and env_ids == slice(None)):
-            return self._ALL_INDICES
-        elif isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        elif isinstance(env_ids, torch.Tensor):
-            return wp.from_torch(env_ids.to(torch.int32), dtype=wp.int32)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self.device, dtype=wp.int32)
 
     def _resolve_mask(self, mask: wp.array | torch.Tensor | None, full_mask: wp.array) -> wp.array:
         """Resolve an environment mask to a warp bool array."""
-        if mask is None:
-            return full_mask
-        if isinstance(mask, torch.Tensor):
-            if mask.dtype != torch.bool:
-                mask = mask.to(torch.bool)
-            return wp.from_torch(mask, dtype=wp.bool)
-        return mask
+        return resolve_1d_mask(mask=mask, all_mask=full_mask, device=self.device)
 
     def _iter_particle_states(self):
         """Yield active Newton states."""
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/kernels.py b/source/isaaclab_newton/isaaclab_newton/assets/kernels.py
index eec3479f1fdc..5733b4d55888 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/kernels.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/kernels.py
@@ -960,6 +960,93 @@ def set_body_link_velocity_to_sim(
     body_acc_w[env_id, body_id] = wp.spatial_vectorf(0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
 
 
+@wp.kernel
+def set_body_com_pose_to_sim_mask(
+    data: wp.array2d(dtype=wp.transformf),
+    body_com_pos_b: wp.array2d(dtype=wp.vec3f),
+    env_mask: wp.array(dtype=wp.bool),
+    body_mask: wp.array(dtype=wp.bool),
+    body_com_pose_w: wp.array2d(dtype=wp.transformf),
+    body_link_pose_w: wp.array2d(dtype=wp.transformf),
+):
+    """Write body COM pose data, and the link poses derived from it, for the selected environments and bodies.
+
+    Args:
+        data: Input array of body COM poses (position [m] and quaternion). Shape is (num_envs, num_bodies).
+        body_com_pos_b: Input array of body COM positions in body frame [m]. Shape is (num_envs, num_bodies).
+        env_mask: Input array of environment mask. Shape is (num_envs,).
+        body_mask: Input array of body mask. Shape is (num_bodies,).
+        body_com_pose_w: Output array where body COM poses (position [m] and quaternion) are written.
+            Shape is (num_envs, num_bodies).
+        body_link_pose_w: Output array where body link poses derived from COM are written (position [m] and
+            quaternion). Shape is (num_envs, num_bodies).
+    """
+    i, j = wp.tid()
+    if env_mask[i] and body_mask[j]:
+        body_com_pose_w[i, j] = data[i, j]
+        body_link_pose_w[i, j] = get_com_pose_in_link_frame_func(body_com_pose_w[i, j], body_com_pos_b[i, j])
+
+
+@wp.kernel
+def set_body_com_velocity_to_sim_mask(
+    data: wp.array2d(dtype=wp.spatial_vectorf),
+    env_mask: wp.array(dtype=wp.bool),
+    body_mask: wp.array(dtype=wp.bool),
+    body_com_velocity_w: wp.array2d(dtype=wp.spatial_vectorf),
+    body_acc_w: wp.array2d(dtype=wp.spatial_vectorf),
+):
+    """Write body COM velocity data, and zero the body accelerations, for the selected environments and bodies.
+
+    Args:
+        data: Input array of body COM spatial velocities [m/s, rad/s]. Shape is (num_envs, num_bodies).
+        env_mask: Input array of environment mask. Shape is (num_envs,).
+        body_mask: Input array of body mask. Shape is (num_bodies,).
+        body_com_velocity_w: Output array where body COM velocities [m/s, rad/s] are written.
+            Shape is (num_envs, num_bodies).
+        body_acc_w: Output array where body accelerations [m/s^2, rad/s^2] are zeroed. Shape is (num_envs, num_bodies).
+    """
+    i, j = wp.tid()
+    if env_mask[i] and body_mask[j]:
+        body_com_velocity_w[i, j] = data[i, j]
+        body_acc_w[i, j] = wp.spatial_vectorf(0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
+
+
+@wp.kernel
+def set_body_link_velocity_to_sim_mask(
+    data: wp.array2d(dtype=wp.spatial_vectorf),
+    body_com_pos_b: wp.array2d(dtype=wp.vec3f),
+    body_link_pose_w: wp.array2d(dtype=wp.transformf),
+    env_mask: wp.array(dtype=wp.bool),
+    body_mask: wp.array(dtype=wp.bool),
+    body_link_velocity_w: wp.array2d(dtype=wp.spatial_vectorf),
+    body_com_velocity_w: wp.array2d(dtype=wp.spatial_vectorf),
+    body_acc_w: wp.array2d(dtype=wp.spatial_vectorf),
+):
+    """Write body link velocity data, the COM velocities derived from it, and zero the body accelerations, for the
+    selected environments and bodies.
+
+    Args:
+        data: Input array of body link spatial velocities [m/s, rad/s]. Shape is (num_envs, num_bodies).
+        body_com_pos_b: Input array of body COM positions in body frame [m]. Shape is (num_envs, num_bodies).
+        body_link_pose_w: Input array of body link poses in world frame (position [m] and quaternion).
+            Shape is (num_envs, num_bodies).
+        env_mask: Input array of environment mask. Shape is (num_envs,).
+        body_mask: Input array of body mask. Shape is (num_bodies,).
+        body_link_velocity_w: Output array where body link velocities [m/s, rad/s] are written.
+            Shape is (num_envs, num_bodies).
+        body_com_velocity_w: Output array where body COM velocities [m/s, rad/s], derived from link, are written.
+            Shape is (num_envs, num_bodies).
+        body_acc_w: Output array where body accelerations [m/s^2, rad/s^2] are zeroed. Shape is (num_envs, num_bodies).
+    """
+    i, j = wp.tid()
+    if env_mask[i] and body_mask[j]:
+        body_link_velocity_w[i, j] = data[i, j]
+        body_com_velocity_w[i, j] = get_link_velocity_in_com_frame_func(
+            body_link_velocity_w[i, j], body_link_pose_w[i, j], body_com_pos_b[i, j]
+        )
+        body_acc_w[i, j] = wp.spatial_vectorf(0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
+
+
 _SET_BODY_LINK_POSE_TO_SIM_DISPATCHER = IndexKernelDispatcher(set_body_link_pose_to_sim, ("env_ids", "body_ids"))
 _SET_BODY_COM_POSE_TO_SIM_DISPATCHER = IndexKernelDispatcher(set_body_com_pose_to_sim, ("env_ids", "body_ids"))
 _SET_BODY_COM_VELOCITY_TO_SIM_DISPATCHER = IndexKernelDispatcher(set_body_com_velocity_to_sim, ("env_ids", "body_ids"))
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/mpm_object/mpm_object.py b/source/isaaclab_newton/isaaclab_newton/assets/mpm_object/mpm_object.py
index bc340f5b7131..430f61eaa3ae 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/mpm_object/mpm_object.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/mpm_object/mpm_object.py
@@ -15,6 +15,7 @@
 
 from isaaclab.assets.deformable_object.base_deformable_object import BaseDeformableObject
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids
 
 from isaaclab_newton.sim.spawners.mpm.mpm import _SIMULATION_POINTS_SUFFIX
 
@@ -283,24 +284,10 @@ def _create_buffers(self):
         self._data.default_particle_state_w = self._data.default_nodal_state_w
 
     def _resolve_env_ids(self, env_ids):
-        if env_ids is None or (isinstance(env_ids, slice) and env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, torch.Tensor):
-            return wp.from_torch(env_ids.to(device=self.device, dtype=torch.int32), dtype=wp.int32)
-        if isinstance(env_ids, Sequence):
-            return wp.array(list(env_ids), dtype=wp.int32, device=self.device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self.device, dtype=wp.int32)
 
     def _resolve_mask(self, mask: wp.array | torch.Tensor | None) -> wp.array:
-        if mask is None:
-            return self._ALL_ENV_MASK
-        if isinstance(mask, torch.Tensor):
-            if mask.dtype != torch.bool:
-                mask = mask.to(torch.bool)
-            return wp.from_torch(mask.to(device=self.device).contiguous(), dtype=wp.bool)
-        return mask
+        return resolve_1d_mask(mask=mask, all_mask=self._ALL_ENV_MASK, device=self.device)
 
     def _iter_particle_states(self):
         """Yield the Newton states whose particle arrays must receive writes."""
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/rigid_object/rigid_object.py b/source/isaaclab_newton/isaaclab_newton/assets/rigid_object/rigid_object.py
index 5a026f669f3e..ee53ff492eb6 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/rigid_object/rigid_object.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/rigid_object/rigid_object.py
@@ -21,6 +21,7 @@
 from isaaclab.assets.rigid_object.base_rigid_object import BaseRigidObject
 from isaaclab.sim.utils.queries import path_expr_to_glob, resolve_matching_prims_from_source
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_ids
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_newton.assets import kernels as shared_kernels
@@ -1122,13 +1123,7 @@ def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array | No
         Returns:
             A warp array of environment indices or a tensor of environment indices.
         """
-        if (env_ids is None) or (env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self.device)
 
     def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
         """Resolve body indices to a warp array or tensor.
@@ -1139,13 +1134,7 @@ def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array |
         Returns:
             A warp array of body indices or a tensor of body indices.
         """
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self.device)
-        if (body_ids is None) or (body_ids == slice(None)):
-            return self._ALL_BODY_INDICES
-        return body_ids
+        return resolve_ids(ids=body_ids, all_ids=self._ALL_BODY_INDICES, device=self.device)
 
     """
     Internal simulation callbacks.
diff --git a/source/isaaclab_newton/isaaclab_newton/assets/rigid_object_collection/rigid_object_collection.py b/source/isaaclab_newton/isaaclab_newton/assets/rigid_object_collection/rigid_object_collection.py
index 15067fe32106..7b37424d4a94 100644
--- a/source/isaaclab_newton/isaaclab_newton/assets/rigid_object_collection/rigid_object_collection.py
+++ b/source/isaaclab_newton/isaaclab_newton/assets/rigid_object_collection/rigid_object_collection.py
@@ -22,6 +22,7 @@
 from isaaclab.assets.rigid_object_collection.base_rigid_object_collection import BaseRigidObjectCollection
 from isaaclab.utils import clone, validate
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids, write_2d_with_mask
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_newton.assets import kernels as shared_kernels
@@ -308,16 +309,8 @@ def write_body_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
-        self.write_body_link_pose_to_sim_index(
-            body_poses=body_poses, env_ids=env_ids, body_ids=body_ids, full_data=True, skip_forward=skip_forward
+        self.write_body_link_pose_to_sim_mask(
+            body_poses=body_poses, body_mask=body_mask, env_mask=env_mask, skip_forward=skip_forward
         )
 
     def write_body_velocity_to_sim_index(
@@ -386,20 +379,8 @@ def write_body_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
-        self.write_body_com_velocity_to_sim_index(
-            body_velocities=body_velocities,
-            env_ids=env_ids,
-            body_ids=body_ids,
-            full_data=True,
-            skip_forward=skip_forward,
+        self.write_body_com_velocity_to_sim_mask(
+            body_velocities=body_velocities, body_mask=body_mask, env_mask=env_mask, skip_forward=skip_forward
         )
 
     def write_body_link_pose_to_sim_index(
@@ -492,16 +473,19 @@ def write_body_link_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_mask = self._ALL_ENV_MASK
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        self.write_body_link_pose_to_sim_index(
-            body_poses=body_poses, env_ids=env_ids, body_ids=body_ids, full_data=True, skip_forward=skip_forward
+        env_mask = resolve_1d_mask(mask=env_mask, all_mask=self._ALL_ENV_MASK, device=self.device)
+        # a body selection given as ids becomes a body mask on the device, so the same mask kernel applies
+        body_mask = resolve_1d_mask(
+            ids=body_ids,
+            mask=body_mask,
+            all_mask=self._ALL_BODY_MASK,
+            scratch_mask=self._scratch_body_mask,
+            device=self.device,
         )
+        self.assert_shape_and_dtype_mask(body_poses, (env_mask, body_mask), wp.transformf, "body_poses")
+        write_2d_with_mask(body_poses, env_mask, body_mask, self.data.body_link_pose_w, self.device)
+        if not skip_forward:
+            self.data._reset_pose(env_mask=env_mask)
 
     def write_body_com_pose_to_sim_index(
         self,
@@ -597,17 +581,25 @@ def write_body_com_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_mask = self._ALL_ENV_MASK
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        # The index writer owns the invalidation (with from_link=False); forward skip_forward to it.
-        self.write_body_com_pose_to_sim_index(
-            body_poses=body_poses, env_ids=env_ids, body_ids=body_ids, full_data=True, skip_forward=skip_forward
+        env_mask = resolve_1d_mask(mask=env_mask, all_mask=self._ALL_ENV_MASK, device=self.device)
+        # a body selection given as ids becomes a body mask on the device, so the same mask kernel applies
+        body_mask = resolve_1d_mask(
+            ids=body_ids,
+            mask=body_mask,
+            all_mask=self._ALL_BODY_MASK,
+            scratch_mask=self._scratch_body_mask,
+            device=self.device,
         )
+        self.assert_shape_and_dtype_mask(body_poses, (env_mask, body_mask), wp.transformf, "body_poses")
+        wp.launch(
+            shared_kernels.set_body_com_pose_to_sim_mask,
+            dim=(env_mask.shape[0], body_mask.shape[0]),
+            inputs=[body_poses, self.data.body_com_pos_b, env_mask, body_mask],
+            outputs=[self.data.body_com_pose_w, self.data.body_link_pose_w],
+            device=self.device,
+        )
+        if not skip_forward:
+            self.data._reset_pose(env_mask=env_mask, from_link=False)
 
     def write_body_com_velocity_to_sim_index(
         self,
@@ -711,21 +703,25 @@ def write_body_com_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_mask = self._ALL_ENV_MASK
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        # The index writer owns the invalidation; forward skip_forward to it.
-        self.write_body_com_velocity_to_sim_index(
-            body_velocities=body_velocities,
-            env_ids=env_ids,
-            body_ids=body_ids,
-            full_data=True,
-            skip_forward=skip_forward,
+        env_mask = resolve_1d_mask(mask=env_mask, all_mask=self._ALL_ENV_MASK, device=self.device)
+        # a body selection given as ids becomes a body mask on the device, so the same mask kernel applies
+        body_mask = resolve_1d_mask(
+            ids=body_ids,
+            mask=body_mask,
+            all_mask=self._ALL_BODY_MASK,
+            scratch_mask=self._scratch_body_mask,
+            device=self.device,
+        )
+        self.assert_shape_and_dtype_mask(body_velocities, (env_mask, body_mask), wp.spatial_vectorf, "body_velocities")
+        wp.launch(
+            shared_kernels.set_body_com_velocity_to_sim_mask,
+            dim=(env_mask.shape[0], body_mask.shape[0]),
+            inputs=[body_velocities, env_mask, body_mask],
+            outputs=[self.data.body_com_vel_w, self.data.body_com_acc_w],
+            device=self.device,
         )
+        if not skip_forward:
+            self.data._reset_velocity(env_mask=env_mask)
 
     def write_body_link_velocity_to_sim_index(
         self,
@@ -831,21 +827,25 @@ def write_body_link_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_mask = self._ALL_ENV_MASK
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        # The index writer owns the invalidation (with from_com=False); forward skip_forward to it.
-        self.write_body_link_velocity_to_sim_index(
-            body_velocities=body_velocities,
-            env_ids=env_ids,
-            body_ids=body_ids,
-            full_data=True,
-            skip_forward=skip_forward,
+        env_mask = resolve_1d_mask(mask=env_mask, all_mask=self._ALL_ENV_MASK, device=self.device)
+        # a body selection given as ids becomes a body mask on the device, so the same mask kernel applies
+        body_mask = resolve_1d_mask(
+            ids=body_ids,
+            mask=body_mask,
+            all_mask=self._ALL_BODY_MASK,
+            scratch_mask=self._scratch_body_mask,
+            device=self.device,
+        )
+        self.assert_shape_and_dtype_mask(body_velocities, (env_mask, body_mask), wp.spatial_vectorf, "body_velocities")
+        wp.launch(
+            shared_kernels.set_body_link_velocity_to_sim_mask,
+            dim=(env_mask.shape[0], body_mask.shape[0]),
+            inputs=[body_velocities, self.data.body_com_pos_b, self.data.body_link_pose_w, env_mask, body_mask],
+            outputs=[self.data.body_link_vel_w, self.data.body_com_vel_w, self.data.body_com_acc_w],
+            device=self.device,
         )
+        if not skip_forward:
+            self.data._reset_velocity(env_mask=env_mask, from_com=False)
 
     """
     Operations - Setters.
@@ -1244,6 +1244,7 @@ def _create_buffers(self):
         )
         self._ALL_ENV_MASK = wp.ones((self.num_instances,), dtype=wp.bool, device=self.device)
         self._ALL_BODY_MASK = wp.ones((self.num_bodies,), dtype=wp.bool, device=self.device)
+        self._scratch_body_mask = wp.zeros((self.num_bodies,), dtype=wp.bool, device=self.device)
 
         # external wrench composer
         self._instantaneous_wrench_composer = WrenchComposer(self)
@@ -1285,13 +1286,7 @@ def _resolve_env_ids(self, env_ids) -> wp.array | torch.Tensor:
         Returns:
             Environment indices.
         """
-        if (env_ids is None) or (env_ids == slice(None)):
-            return self._ALL_ENV_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_ENV_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_ENV_INDICES, device=self.device)
 
     def _resolve_body_ids(self, body_ids) -> wp.array | torch.Tensor:
         """Resolve body indices.
@@ -1302,37 +1297,7 @@ def _resolve_body_ids(self, body_ids) -> wp.array | torch.Tensor:
         Returns:
             Body indices.
         """
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self.device)
-        if (body_ids is None) or (body_ids == slice(None)):
-            return self._ALL_BODY_INDICES
-        if isinstance(body_ids, slice):
-            return wp.from_torch(
-                torch.arange(self.num_bodies, dtype=torch.int32, device=self.device)[body_ids], dtype=wp.int32
-            )
-        return body_ids
-
-    def _resolve_env_mask(self, env_mask: wp.array | None) -> wp.array | torch.Tensor:
-        """Resolve environment mask to indices via torch.nonzero."""
-        if env_mask is not None:
-            if isinstance(env_mask, wp.array):
-                env_mask = wp.to_torch(env_mask)
-            env_ids = torch.nonzero(env_mask)[:, 0]
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        return env_ids
-
-    def _resolve_body_mask(self, body_mask: wp.array | None) -> wp.array | torch.Tensor:
-        """Resolve body mask to indices via torch.nonzero."""
-        if body_mask is not None:
-            if isinstance(body_mask, wp.array):
-                body_mask = wp.to_torch(body_mask)
-            body_ids = torch.nonzero(body_mask)[:, 0]
-        else:
-            body_ids = self._ALL_BODY_INDICES
-        return body_ids
+        return resolve_ids(ids=body_ids, all_ids=self._ALL_BODY_INDICES, device=self.device)
 
     """
     Internal simulation callbacks.
diff --git a/source/isaaclab_newton/test/assets/test_articulation.py b/source/isaaclab_newton/test/assets/test_articulation.py
index 20e39199a7d8..344967e0599b 100644
--- a/source/isaaclab_newton/test/assets/test_articulation.py
+++ b/source/isaaclab_newton/test/assets/test_articulation.py
@@ -663,6 +663,28 @@ def test_hard_reset_recreates_ordered_state_and_actuators(device: str) -> None:
                 assert not torch.equal(articulation.data.joint_pos.torch, position)
 
 
+@pytest.mark.parametrize("device", test_devices(DeviceScope.CUDA))
+def test_fixed_tendon_mask_writer_reaches_solver_on_every_replay(device: str) -> None:
+    """Each replay of a CUDA graph holding the fixed-tendon mask writer refreshes the solver's tendon properties.
+
+    The solver keeps its own copy of them, so a refresh queued only while capturing would leave the physics on the
+    values of the first replay.
+    """
+    with build_simulation_context(sim_cfg=newton_sim_cfg(device, use_newton_actuators=False)) as sim:
+        articulation = spawn_assets({"tendon": _island_cfgs()["tendon"]})["tendon"]
+        sim.reset()
+        stiffness = torch.zeros(articulation.num_instances, articulation.num_fixed_tendons, device=device)
+        with wp.ScopedCapture(device) as capture:
+            articulation.set_fixed_tendon_stiffness_mask(stiffness=stiffness)
+            articulation.write_fixed_tendon_properties_to_sim_mask()
+        solver_model = sim.backend_manager.backend.solver.mjw_model
+        for value in (12.0, 34.0):
+            stiffness.fill_(value)
+            wp.capture_launch(capture.graph)
+            sim.step()
+            np.testing.assert_allclose(solver_model.tendon_stiffness.numpy(), value)
+
+
 @pytest.mark.parametrize("device", test_devices(DeviceScope.CUDA))
 def test_newton_ordered_state_publishes_inside_captured_cuda_graph(device: str) -> None:
     """Republish the user-order state shadows from inside a captured CUDA graph.
diff --git a/source/isaaclab_ov/changelog.d/jichuanh-id-mask.changed.rst b/source/isaaclab_ov/changelog.d/jichuanh-id-mask.changed.rst
new file mode 100644
index 000000000000..3f1ff2245d66
--- /dev/null
+++ b/source/isaaclab_ov/changelog.d/jichuanh-id-mask.changed.rst
@@ -0,0 +1,7 @@
+* Changed the env selection helpers of the OVPhysX assets to resolve ``env_ids`` through
+  :func:`~isaaclab.utils.warp.utils.resolve_ids` and ``env_mask`` through
+  :func:`~isaaclab.utils.warp.utils.resolve_1d_mask`. Any integer sequence and slices with a negative step are accepted,
+  and a :class:`~isaaclab.utils.warp.ProxyArray` is rejected with a :class:`TypeError`.
+* Changed the body, joint and tendon selection helpers of the OVPhysX assets to resolve ids and masks through
+  :func:`~isaaclab.utils.warp.utils.resolve_ids` and :func:`~isaaclab.utils.warp.utils.resolve_1d_mask`, as the env
+  selection does, so slices other than ``slice(None)`` are accepted.
diff --git a/source/isaaclab_ov/isaaclab_ov/assets/articulation/articulation.py b/source/isaaclab_ov/isaaclab_ov/assets/articulation/articulation.py
index 07bc71d3f611..2162ae04b8ba 100644
--- a/source/isaaclab_ov/isaaclab_ov/assets/articulation/articulation.py
+++ b/source/isaaclab_ov/isaaclab_ov/assets/articulation/articulation.py
@@ -33,6 +33,7 @@
 from isaaclab.utils.string import resolve_matching_names
 from isaaclab.utils.warp import ProxyArray
 from isaaclab.utils.warp import kernels as warp_kernels
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_ov import tensor_types as TT
@@ -4373,79 +4374,27 @@ def _log_articulation_info(self) -> None:
 
     def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
         """Resolve environment indices on ``self._device``."""
-        if env_ids is None or (isinstance(env_ids, slice) and env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self._device)
-        if isinstance(env_ids, torch.Tensor):
-            return env_ids.to(device=self._device)
-        if isinstance(env_ids, wp.array) and str(env_ids.device) != self._device:
-            env_ids = wp.clone(env_ids, device=self._device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self._device)
 
     def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
         """Resolve body indices to a Warp signed-integer array on ``self._device``."""
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if body_ids is None or body_ids == slice(None):
-            return self._ALL_BODY_INDICES
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self._device)
-        if isinstance(body_ids, torch.Tensor):
-            return body_ids.to(device=self._device)
-        if isinstance(body_ids, wp.array) and str(body_ids.device) != self._device:
-            body_ids = wp.clone(body_ids, device=self._device)
-        return body_ids
+        return resolve_ids(ids=body_ids, all_ids=self._ALL_BODY_INDICES, device=self._device)
 
     def _resolve_joint_ids(self, joint_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
         """Resolve joint indices to a Warp signed-integer array on ``self._device``."""
-        if isinstance(joint_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if joint_ids is None or joint_ids == slice(None):
-            return self._ALL_JOINT_INDICES
-        if isinstance(joint_ids, list):
-            return wp.array(joint_ids, dtype=wp.int32, device=self._device)
-        if isinstance(joint_ids, torch.Tensor):
-            return joint_ids.to(device=self._device)
-        if isinstance(joint_ids, wp.array) and str(joint_ids.device) != self._device:
-            joint_ids = wp.clone(joint_ids, device=self._device)
-        return joint_ids
+        return resolve_ids(ids=joint_ids, all_ids=self._ALL_JOINT_INDICES, device=self._device)
 
     def _resolve_fixed_tendon_ids(
         self, tendon_ids: Sequence[int] | torch.Tensor | wp.array | None
     ) -> wp.array | torch.Tensor:
         """Resolve fixed-tendon indices to a Warp signed-integer array on ``self._device``."""
-        if isinstance(tendon_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if tendon_ids is None or tendon_ids == slice(None):
-            return self._ALL_FIXED_TENDON_INDICES
-        if isinstance(tendon_ids, list):
-            return wp.array(tendon_ids, dtype=wp.int32, device=self._device)
-        if isinstance(tendon_ids, torch.Tensor):
-            return tendon_ids.to(device=self._device)
-        if isinstance(tendon_ids, wp.array) and str(tendon_ids.device) != self._device:
-            tendon_ids = wp.clone(tendon_ids, device=self._device)
-        return tendon_ids
+        return resolve_ids(ids=tendon_ids, all_ids=self._ALL_FIXED_TENDON_INDICES, device=self._device)
 
     def _resolve_spatial_tendon_ids(
         self, tendon_ids: Sequence[int] | torch.Tensor | wp.array | None
     ) -> wp.array | torch.Tensor:
         """Resolve spatial-tendon indices to a Warp signed-integer array on ``self._device``."""
-        if isinstance(tendon_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if tendon_ids is None or tendon_ids == slice(None):
-            return self._ALL_SPATIAL_TENDON_INDICES
-        if isinstance(tendon_ids, list):
-            return wp.array(tendon_ids, dtype=wp.int32, device=self._device)
-        if isinstance(tendon_ids, torch.Tensor):
-            return tendon_ids.to(device=self._device)
-        if isinstance(tendon_ids, wp.array) and str(tendon_ids.device) != self._device:
-            tendon_ids = wp.clone(tendon_ids, device=self._device)
-        return tendon_ids
+        return resolve_ids(ids=tendon_ids, all_ids=self._ALL_SPATIAL_TENDON_INDICES, device=self._device)
 
     def _broadcast_scalar_to_2d(
         self, value: float | torch.Tensor | wp.array, shape: tuple[int, int]
@@ -4483,13 +4432,7 @@ def _resolve_env_mask(self, env_mask: wp.array | None) -> wp.array:
         no ``torch.nonzero`` conversion is needed. ``None`` returns the pre-allocated
         all-true mask.
         """
-        if env_mask is None:
-            return self._ALL_TRUE_ENV_MASK
-        if isinstance(env_mask, torch.Tensor):
-            return wp.from_torch(env_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(env_mask, wp.array) and str(env_mask.device) != self._device:
-            env_mask = wp.clone(env_mask, device=self._device)
-        return env_mask
+        return resolve_1d_mask(mask=env_mask, all_mask=self._ALL_TRUE_ENV_MASK, device=self._device)
 
     def _sim_env_ids_view(self, count: int) -> wp.array:
         """Return a cached prefix view of the simulator-index scratch buffer."""
@@ -4505,43 +4448,19 @@ def _sim_env_ids_view(self, count: int) -> wp.array:
 
     def _resolve_body_mask(self, body_mask: wp.array | None) -> wp.array:
         """Resolve a body mask to a ``wp.bool`` array on ``self._device`` (Newton-style)."""
-        if body_mask is None:
-            return self._ALL_TRUE_BODY_MASK
-        if isinstance(body_mask, torch.Tensor):
-            return wp.from_torch(body_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(body_mask, wp.array) and str(body_mask.device) != self._device:
-            body_mask = wp.clone(body_mask, device=self._device)
-        return body_mask
+        return resolve_1d_mask(mask=body_mask, all_mask=self._ALL_TRUE_BODY_MASK, device=self._device)
 
     def _resolve_joint_mask(self, joint_mask: wp.array | None) -> wp.array:
         """Resolve a joint mask to a ``wp.bool`` array on ``self._device``."""
-        if joint_mask is None:
-            return self._ALL_TRUE_JOINT_MASK
-        if isinstance(joint_mask, torch.Tensor):
-            return wp.from_torch(joint_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(joint_mask, wp.array) and str(joint_mask.device) != self._device:
-            joint_mask = wp.clone(joint_mask, device=self._device)
-        return joint_mask
+        return resolve_1d_mask(mask=joint_mask, all_mask=self._ALL_TRUE_JOINT_MASK, device=self._device)
 
     def _resolve_fixed_tendon_mask(self, tendon_mask: wp.array | None) -> wp.array:
         """Resolve a fixed-tendon mask to a ``wp.bool`` array on ``self._device``."""
-        if tendon_mask is None:
-            return self._ALL_TRUE_FIXED_TENDON_MASK
-        if isinstance(tendon_mask, torch.Tensor):
-            return wp.from_torch(tendon_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(tendon_mask, wp.array) and str(tendon_mask.device) != self._device:
-            tendon_mask = wp.clone(tendon_mask, device=self._device)
-        return tendon_mask
+        return resolve_1d_mask(mask=tendon_mask, all_mask=self._ALL_TRUE_FIXED_TENDON_MASK, device=self._device)
 
     def _resolve_spatial_tendon_mask(self, tendon_mask: wp.array | None) -> wp.array:
         """Resolve a spatial-tendon mask to a ``wp.bool`` array on ``self._device``."""
-        if tendon_mask is None:
-            return self._ALL_TRUE_SPATIAL_TENDON_MASK
-        if isinstance(tendon_mask, torch.Tensor):
-            return wp.from_torch(tendon_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(tendon_mask, wp.array) and str(tendon_mask.device) != self._device:
-            tendon_mask = wp.clone(tendon_mask, device=self._device)
-        return tendon_mask
+        return resolve_1d_mask(mask=tendon_mask, all_mask=self._ALL_TRUE_SPATIAL_TENDON_MASK, device=self._device)
 
     def _get_cpu_env_mask(self, env_mask: wp.array) -> wp.array:
         """Return a pinned-host CPU copy of :paramref:`env_mask` for a CPU-only binding write.
diff --git a/source/isaaclab_ov/isaaclab_ov/assets/deformable_object/deformable_object.py b/source/isaaclab_ov/isaaclab_ov/assets/deformable_object/deformable_object.py
index ccca84b3cd0a..ceef9f0e2049 100644
--- a/source/isaaclab_ov/isaaclab_ov/assets/deformable_object/deformable_object.py
+++ b/source/isaaclab_ov/isaaclab_ov/assets/deformable_object/deformable_object.py
@@ -22,6 +22,7 @@
 from isaaclab.assets.deformable_object.base_deformable_object import BaseDeformableObject
 from isaaclab.markers import VisualizationMarkers
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_ids
 
 from isaaclab_ov import tensor_types as TT
 from isaaclab_ov.sim.views.ovphysx_view import OvPhysxView
@@ -528,22 +529,7 @@ def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array(dtyp
         dtype=wp.int32
     ):
         """Resolve environment indices to a device-resident int32 Warp array."""
-        if env_ids is None or (isinstance(env_ids, slice) and env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            # OVPhysX consumes these IDs directly and requires contiguous DLPack tensors.
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids].contiguous())
-        if isinstance(env_ids, torch.Tensor):
-            values = env_ids.to(device=self.device, dtype=torch.int32).contiguous()
-            return wp.from_torch(values, dtype=wp.int32)
-        if isinstance(env_ids, wp.array):
-            if env_ids.dtype != wp.int32:
-                values = wp.to_torch(env_ids).to(device=self.device, dtype=torch.int32).contiguous()
-                return wp.from_torch(values, dtype=wp.int32)
-            if str(env_ids.device) != self.device:
-                return wp.clone(env_ids, device=self.device)
-            return env_ids
-        return wp.array(list(env_ids), dtype=wp.int32, device=self.device)
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self.device, dtype=wp.int32)
 
     @staticmethod
     def _arrays_overlap(first: wp.array, second: wp.array) -> bool:
diff --git a/source/isaaclab_ov/isaaclab_ov/assets/rigid_object/rigid_object.py b/source/isaaclab_ov/isaaclab_ov/assets/rigid_object/rigid_object.py
index 7e19bc75109d..a44665429701 100644
--- a/source/isaaclab_ov/isaaclab_ov/assets/rigid_object/rigid_object.py
+++ b/source/isaaclab_ov/isaaclab_ov/assets/rigid_object/rigid_object.py
@@ -22,6 +22,7 @@
 from isaaclab.sim.utils.queries import path_expr_to_glob, resolve_matching_prims_from_source
 from isaaclab.utils.string import resolve_matching_names
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_ov import tensor_types as TT
@@ -1076,17 +1077,7 @@ def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array | No
         Returns:
             Environment indices on ``self._device``.
         """
-        if env_ids is None or env_ids == slice(None):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self._device)
-        if isinstance(env_ids, torch.Tensor):
-            return env_ids.to(device=self._device)
-        if isinstance(env_ids, wp.array) and str(env_ids.device) != self._device:
-            env_ids = wp.clone(env_ids, device=self._device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self._device)
 
     def _sim_env_ids_view(self, count: int) -> wp.array:
         """Return a cached prefix of the simulator-index scratch buffer."""
@@ -1109,13 +1100,7 @@ def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array |
         Returns:
             Body indices.
         """
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if body_ids is None or body_ids == slice(None):
-            return self._ALL_BODY_INDICES
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self._device)
-        return body_ids
+        return resolve_ids(ids=body_ids, all_ids=self._ALL_BODY_INDICES, device=self._device)
 
     def _resolve_env_mask(self, env_mask: wp.array | None) -> wp.array:
         """Resolve an environment mask to a ``wp.bool`` array.
@@ -1126,13 +1111,7 @@ def _resolve_env_mask(self, env_mask: wp.array | None) -> wp.array:
         Returns:
             A warp ``wp.bool`` array on ``self._device``.
         """
-        if env_mask is None:
-            return self._ALL_TRUE_ENV_MASK
-        if isinstance(env_mask, torch.Tensor):
-            return wp.from_torch(env_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(env_mask, wp.array) and str(env_mask.device) != self._device:
-            env_mask = wp.clone(env_mask, device=self._device)
-        return env_mask
+        return resolve_1d_mask(mask=env_mask, all_mask=self._ALL_TRUE_ENV_MASK, device=self._device)
 
     def _resolve_body_mask(self, body_mask: wp.array | None) -> wp.array:
         """Resolve a body mask to a ``wp.bool`` array.
@@ -1143,13 +1122,7 @@ def _resolve_body_mask(self, body_mask: wp.array | None) -> wp.array:
         Returns:
             A warp ``wp.bool`` array on ``self._device``.
         """
-        if body_mask is None:
-            return self._ALL_TRUE_BODY_MASK
-        if isinstance(body_mask, torch.Tensor):
-            return wp.from_torch(body_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(body_mask, wp.array) and str(body_mask.device) != self._device:
-            body_mask = wp.clone(body_mask, device=self._device)
-        return body_mask
+        return resolve_1d_mask(mask=body_mask, all_mask=self._ALL_TRUE_BODY_MASK, device=self._device)
 
     def _get_cpu_env_mask(self, env_mask: wp.array) -> wp.array:
         """Return a pinned-host CPU copy of *env_mask* for a CPU-only binding write.
diff --git a/source/isaaclab_ov/isaaclab_ov/assets/rigid_object_collection/rigid_object_collection.py b/source/isaaclab_ov/isaaclab_ov/assets/rigid_object_collection/rigid_object_collection.py
index c39c8c6d2f2b..d4fac59b9a4e 100644
--- a/source/isaaclab_ov/isaaclab_ov/assets/rigid_object_collection/rigid_object_collection.py
+++ b/source/isaaclab_ov/isaaclab_ov/assets/rigid_object_collection/rigid_object_collection.py
@@ -21,6 +21,7 @@
 from isaaclab.utils import clone, validate
 from isaaclab.utils.string import resolve_matching_names
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_1d_mask, resolve_ids
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_ov import tensor_types as TT
@@ -439,16 +440,8 @@ def write_body_link_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_mask_t = wp.to_torch(env_mask) if isinstance(env_mask, wp.array) else env_mask
-            env_ids = self._resolve_env_ids(torch.nonzero(env_mask_t)[:, 0])
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_mask_t = wp.to_torch(body_mask) if isinstance(body_mask, wp.array) else body_mask
-            body_ids = self._resolve_body_ids(torch.nonzero(body_mask_t)[:, 0])
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         self.assert_shape_and_dtype(body_poses, (self._num_instances, self._num_bodies), wp.transformf, "body_poses")
         wp.launch(
             shared_kernels.set_body_link_pose_to_sim_kernel(env_ids, body_ids),
@@ -535,16 +528,8 @@ def write_body_com_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_mask_t = wp.to_torch(env_mask) if isinstance(env_mask, wp.array) else env_mask
-            env_ids = self._resolve_env_ids(torch.nonzero(env_mask_t)[:, 0])
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_mask_t = wp.to_torch(body_mask) if isinstance(body_mask, wp.array) else body_mask
-            body_ids = self._resolve_body_ids(torch.nonzero(body_mask_t)[:, 0])
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         self.assert_shape_and_dtype(body_poses, (self._num_instances, self._num_bodies), wp.transformf, "body_poses")
         wp.launch(
             shared_kernels.set_body_com_pose_to_sim_kernel(env_ids, body_ids),
@@ -643,16 +628,8 @@ def write_body_com_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_mask_t = wp.to_torch(env_mask) if isinstance(env_mask, wp.array) else env_mask
-            env_ids = self._resolve_env_ids(torch.nonzero(env_mask_t)[:, 0])
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_mask_t = wp.to_torch(body_mask) if isinstance(body_mask, wp.array) else body_mask
-            body_ids = self._resolve_body_ids(torch.nonzero(body_mask_t)[:, 0])
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         self.assert_shape_and_dtype(
             body_velocities, (self._num_instances, self._num_bodies), wp.spatial_vectorf, "body_velocities"
         )
@@ -758,16 +735,8 @@ def write_body_link_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_mask_t = wp.to_torch(env_mask) if isinstance(env_mask, wp.array) else env_mask
-            env_ids = self._resolve_env_ids(torch.nonzero(env_mask_t)[:, 0])
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_mask_t = wp.to_torch(body_mask) if isinstance(body_mask, wp.array) else body_mask
-            body_ids = self._resolve_body_ids(torch.nonzero(body_mask_t)[:, 0])
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         self.assert_shape_and_dtype(
             body_velocities, (self._num_instances, self._num_bodies), wp.spatial_vectorf, "body_velocities"
         )
@@ -869,11 +838,7 @@ def set_masses_mask(
             env_mask: Environment mask. If None, all instances are updated.
                 Shape is (num_instances,).
         """
-        if env_mask is not None:
-            env_mask_t = wp.to_torch(env_mask) if isinstance(env_mask, wp.array) else env_mask
-            env_ids = self._resolve_env_ids(torch.nonzero(env_mask_t)[:, 0])
-        else:
-            env_ids = self._ALL_ENV_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.assert_shape_and_dtype(masses, (self._num_instances, self._num_bodies), wp.float32, "masses")
         wp.launch(
             shared_kernels.write_2d_data_to_buffer_with_mask,
@@ -955,11 +920,7 @@ def set_coms_mask(
             env_mask: Environment mask. If None, all instances are updated.
                 Shape is (num_instances,).
         """
-        if env_mask is not None:
-            env_mask_t = wp.to_torch(env_mask) if isinstance(env_mask, wp.array) else env_mask
-            env_ids = self._resolve_env_ids(torch.nonzero(env_mask_t)[:, 0])
-        else:
-            env_ids = self._ALL_ENV_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.assert_shape_and_dtype(coms, (self._num_instances, self._num_bodies), wp.transformf, "coms")
         wp.launch(
             shared_kernels.write_body_com_pose_to_buffer_mask,
@@ -1051,11 +1012,7 @@ def set_inertias_mask(
             env_mask: Environment mask. If None, all instances are updated.
                 Shape is (num_instances,).
         """
-        if env_mask is not None:
-            env_mask_t = wp.to_torch(env_mask) if isinstance(env_mask, wp.array) else env_mask
-            env_ids = self._resolve_env_ids(torch.nonzero(env_mask_t)[:, 0])
-        else:
-            env_ids = self._ALL_ENV_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.assert_shape_and_dtype(inertias, (self._num_instances, self._num_bodies, 9), wp.float32, "inertias")
         wp.launch(
             shared_kernels.write_body_inertia_to_buffer_mask,
@@ -1381,34 +1338,18 @@ def _binding_write(
     Internal helper.
     """
 
-    def _resolve_env_ids(self, env_ids) -> wp.array | torch.Tensor:
+    def _resolve_env_ids(self, env_ids=None, env_mask: wp.array | None = None) -> wp.array | torch.Tensor:
         """Resolve environment indices on ``self._device``.
 
         Tests sometimes hand us indices on CPU even when the sim runs on GPU; we move the
         resolved array onto ``self._device`` so kernel launches don't fail on a device
         mismatch.
         """
-        if env_ids is None or env_ids == slice(None):
-            return self._ALL_ENV_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_ENV_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self._device)
-        if isinstance(env_ids, torch.Tensor):
-            return env_ids.to(device=self._device)
-        if isinstance(env_ids, wp.array) and str(env_ids.device) != self._device:
-            env_ids = wp.clone(env_ids, device=self._device)
-        return env_ids
+        return resolve_ids(ids=env_ids, mask=env_mask, all_ids=self._ALL_ENV_INDICES, device=self._device)
 
-    def _resolve_body_ids(self, body_ids) -> wp.array | torch.Tensor:
+    def _resolve_body_ids(self, body_ids=None, body_mask: wp.array | None = None) -> wp.array | torch.Tensor:
         """Resolve body indices on ``self._device``."""
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if body_ids is None or body_ids == slice(None):
-            return self._ALL_BODY_INDICES
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self._device)
-        return body_ids
+        return resolve_ids(ids=body_ids, mask=body_mask, all_ids=self._ALL_BODY_INDICES, device=self._device)
 
     def _env_body_ids_to_view_ids(
         self, env_ids: torch.Tensor | wp.array, body_ids: torch.Tensor | wp.array, device: str = "cuda:0"
@@ -1418,6 +1359,8 @@ def _env_body_ids_to_view_ids(
         Computes ``view_id = body_id * num_instances + env_id`` for each
         (env_id, body_id) pair.  The output array is laid out column-major over
         the (env, body) grid, matching the PhysX ``root_view`` ordering.
+        The mask writers convert their masks to ids for this: a binding write mask must cover all
+        ``num_bodies * num_instances`` rows, so an env mask does not fit.
 
         Args:
             env_ids: Environment indices.
@@ -1466,13 +1409,7 @@ def _resolve_env_mask(self, env_mask: wp.array | None) -> wp.array:
         Returns:
             A ``wp.bool`` array of shape (num_instances,) on ``self._device``.
         """
-        if env_mask is None:
-            return self._ALL_TRUE_ENV_MASK
-        if isinstance(env_mask, torch.Tensor):
-            return wp.from_torch(env_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(env_mask, wp.array) and str(env_mask.device) != self._device:
-            env_mask = wp.clone(env_mask, device=self._device)
-        return env_mask
+        return resolve_1d_mask(mask=env_mask, all_mask=self._ALL_TRUE_ENV_MASK, device=self._device)
 
     def _resolve_body_mask(self, body_mask: wp.array | None) -> wp.array:
         """Resolve a body mask to a ``wp.bool`` array on ``self._device``.
@@ -1485,13 +1422,7 @@ def _resolve_body_mask(self, body_mask: wp.array | None) -> wp.array:
         Returns:
             A ``wp.bool`` array of shape (num_bodies,) on ``self._device``.
         """
-        if body_mask is None:
-            return self._ALL_TRUE_BODY_MASK
-        if isinstance(body_mask, torch.Tensor):
-            return wp.from_torch(body_mask.to(torch.bool), dtype=wp.bool)
-        if isinstance(body_mask, wp.array) and str(body_mask.device) != self._device:
-            body_mask = wp.clone(body_mask, device=self._device)
-        return body_mask
+        return resolve_1d_mask(mask=body_mask, all_mask=self._ALL_TRUE_BODY_MASK, device=self._device)
 
     def _sim_env_ids_view(self, count: int) -> wp.array:
         """Return a cached prefix of the simulator-index scratch buffer."""
diff --git a/source/isaaclab_ov/test/assets/test_deformable_object.py b/source/isaaclab_ov/test/assets/test_deformable_object.py
index 7a2f90460fae..38e32c3f9041 100644
--- a/source/isaaclab_ov/test/assets/test_deformable_object.py
+++ b/source/isaaclab_ov/test/assets/test_deformable_object.py
@@ -386,6 +386,28 @@ def test_indexed_partial_write_preserves_retained_aliased_slice(
     torch.testing.assert_close(retained.torch, expected)
 
 
+@pytest.mark.usefixtures("host_shell")
+def test_mask_writes_update_only_masked_rows():
+    """The mask writers take full-size data and write only the environments the mask selects."""
+    asset = _make_asset_shell(deformable_type="volume", num_instances=3, num_vertices=2)
+    zeros = torch.zeros((3, 2, 3), device=asset.device)
+    asset.root_view.positions = wp.from_torch(zeros.clone(), dtype=wp.float32)
+    asset.root_view.velocities = wp.from_torch(zeros.clone(), dtype=wp.float32)
+    asset.update(0.1)
+    env_mask = wp.array([False, True, False], dtype=wp.bool, device=asset.device)
+
+    state = torch.cat((torch.full((3, 2, 3), 5.0), torch.full((3, 2, 3), -5.0)), dim=-1).to(asset.device)
+    asset.write_nodal_state_to_sim_mask(state, env_mask=env_mask)
+    expected = torch.zeros((3, 2, 6), device=asset.device)
+    expected[1] = state[1]
+    torch.testing.assert_close(asset.data.nodal_state_w.torch, expected)
+
+    positions = torch.full((3, 2, 3), 9.0, device=asset.device)
+    asset.write_nodal_pos_to_sim_mask(positions, env_mask=env_mask)
+    expected[1, :, :3] = 9.0
+    torch.testing.assert_close(asset.data.nodal_pos_w.torch, expected[..., :3])
+
+
 @pytest.mark.usefixtures("host_shell")
 def test_full_overwrite_stale_cache_does_not_read_simulator() -> None:
     asset = _make_asset_shell(deformable_type="volume", num_instances=3, num_vertices=2)
diff --git a/source/isaaclab_physx/changelog.d/jichuanh-id-mask.changed.rst b/source/isaaclab_physx/changelog.d/jichuanh-id-mask.changed.rst
new file mode 100644
index 000000000000..fb8da731a750
--- /dev/null
+++ b/source/isaaclab_physx/changelog.d/jichuanh-id-mask.changed.rst
@@ -0,0 +1,7 @@
+* Changed the env selection helpers of the PhysX assets to resolve ``env_ids`` through
+  :func:`~isaaclab.utils.warp.utils.resolve_ids`. Any integer sequence and slices with a negative step are accepted,
+  ids on another device are moved to the asset's device, and a :class:`~isaaclab.utils.warp.ProxyArray` is rejected
+  with a :class:`TypeError`.
+* Changed the body, joint and tendon selection helpers of the PhysX assets to resolve ids and masks through
+  :func:`~isaaclab.utils.warp.utils.resolve_ids`, as the env selection does, so slices other than ``slice(None)`` are
+  accepted.
diff --git a/source/isaaclab_physx/changelog.d/jichuanh-id-mask.fixed.rst b/source/isaaclab_physx/changelog.d/jichuanh-id-mask.fixed.rst
new file mode 100644
index 000000000000..96c018a902e7
--- /dev/null
+++ b/source/isaaclab_physx/changelog.d/jichuanh-id-mask.fixed.rst
@@ -0,0 +1,2 @@
+* Fixed the ``write_nodal_*_to_sim_mask`` methods of :class:`~isaaclab_physx.assets.DeformableObject` raising a
+  :class:`RuntimeError` whenever ``env_mask`` was given.
diff --git a/source/isaaclab_physx/isaaclab_physx/assets/articulation/articulation.py b/source/isaaclab_physx/isaaclab_physx/assets/articulation/articulation.py
index 3d2cb4f1d946..b1be80852be8 100644
--- a/source/isaaclab_physx/isaaclab_physx/assets/articulation/articulation.py
+++ b/source/isaaclab_physx/isaaclab_physx/assets/articulation/articulation.py
@@ -27,6 +27,7 @@
 from isaaclab.utils.string import resolve_matching_names, resolve_matching_names_values
 from isaaclab.utils.version import get_isaac_sim_version, has_kit
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_ids
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_physx.assets import kernels as shared_kernels
@@ -590,7 +591,7 @@ def write_root_link_pose_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         # Set full data to True to ensure the the right code path is taken inside the kernel.
         self.write_root_link_pose_to_sim_index(
             root_pose=root_pose, env_ids=env_ids, full_data=True, skip_forward=skip_forward
@@ -692,7 +693,7 @@ def write_root_com_pose_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         # Set full data to True to ensure the the right code path is taken inside the kernel.
         self.write_root_com_pose_to_sim_index(
             root_pose=root_pose, env_ids=env_ids, full_data=True, skip_forward=skip_forward
@@ -866,7 +867,7 @@ def write_root_com_velocity_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         # Set full data to True to ensure the the right code path is taken inside the kernel.
         self.write_root_com_velocity_to_sim_index(
             root_velocity=root_velocity, env_ids=env_ids, full_data=True, skip_forward=skip_forward
@@ -977,7 +978,7 @@ def write_root_link_velocity_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         # Set full data to True to ensure the the right code path is taken inside the kernel.
         self.write_root_link_velocity_to_sim_index(
             root_velocity=root_velocity, env_ids=env_ids, full_data=True, skip_forward=skip_forward
@@ -1091,8 +1092,8 @@ def write_joint_state_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
         # set into simulation
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = None if joint_mask is None else self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = None if joint_mask is None else self._resolve_joint_ids(joint_mask=joint_mask)
         self.write_joint_state_to_sim_index(
             position=position,
             velocity=velocity,
@@ -1196,8 +1197,8 @@ def write_joint_position_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = None if joint_mask is None else self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = None if joint_mask is None else self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the the right code path is taken inside the kernel.
         self.write_joint_position_to_sim_index(
             position=position, joint_ids=joint_ids, env_ids=env_ids, full_data=True, skip_forward=skip_forward
@@ -1301,8 +1302,8 @@ def write_joint_velocity_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = None if joint_mask is None else self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = None if joint_mask is None else self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the the right code path is taken inside the kernel.
         self.write_joint_velocity_to_sim_index(
             velocity=velocity, joint_ids=joint_ids, env_ids=env_ids, full_data=True, skip_forward=skip_forward
@@ -1412,8 +1413,8 @@ def write_joint_stiffness_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the the right code path is taken inside the kernel.
         self.write_joint_stiffness_to_sim_index(
             stiffness=stiffness, joint_ids=joint_ids, env_ids=env_ids, full_data=True
@@ -1560,8 +1561,8 @@ def write_joint_damping_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_damping_to_sim_index(damping=damping, joint_ids=joint_ids, env_ids=env_ids, full_data=True)
 
@@ -1672,8 +1673,8 @@ def write_joint_position_limit_to_sim_mask(
                 exceed the new limits. Defaults to True.
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_position_limit_to_sim_index(
             limits=limits,
@@ -1787,8 +1788,8 @@ def write_joint_velocity_limit_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_velocity_limit_to_sim_index(
             limits=limits, joint_ids=joint_ids, env_ids=env_ids, full_data=True
@@ -1897,8 +1898,8 @@ def write_joint_effort_limit_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_effort_limit_to_sim_index(limits=limits, joint_ids=joint_ids, env_ids=env_ids, full_data=True)
 
@@ -2005,8 +2006,8 @@ def write_joint_armature_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_armature_to_sim_index(armature=armature, joint_ids=joint_ids, env_ids=env_ids, full_data=True)
 
@@ -2173,8 +2174,8 @@ def write_joint_friction_coefficient_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_friction_coefficient_to_sim_index(
             joint_friction_coeff=joint_friction_coeff,
@@ -2283,8 +2284,8 @@ def write_joint_dynamic_friction_coefficient_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_dynamic_friction_coefficient_to_sim_index(
             joint_dynamic_friction_coeff=joint_dynamic_friction_coeff,
@@ -2394,8 +2395,8 @@ def write_joint_viscous_friction_coefficient_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # resolve masks
-        env_ids = self._resolve_env_mask(env_mask)
-        joint_ids = self._resolve_joint_mask(joint_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        joint_ids = self._resolve_joint_ids(joint_mask=joint_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.write_joint_viscous_friction_coefficient_to_sim_index(
             joint_viscous_friction_coeff=joint_viscous_friction_coeff,
@@ -2496,8 +2497,8 @@ def set_masses_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        body_ids = self._resolve_body_mask(body_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_masses_index(masses=masses, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -2603,8 +2604,8 @@ def set_coms_mask(
         all_envs_selected = env_mask is None
         all_bodies_selected = body_mask is None
         # Resolve masks.
-        env_ids = None if all_envs_selected else self._resolve_env_mask(env_mask)
-        body_ids = None if all_bodies_selected else self._resolve_body_mask(body_mask)
+        env_ids = None if all_envs_selected else self._resolve_env_ids(env_mask=env_mask)
+        body_ids = None if all_bodies_selected else self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_coms_index(coms=coms, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -2700,8 +2701,8 @@ def set_inertias_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        body_ids = self._resolve_body_mask(body_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_inertias_index(inertias=inertias, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -2806,8 +2807,8 @@ def set_fixed_tendon_stiffness_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        fixed_tendon_ids = self._resolve_fixed_tendon_ids(fixed_tendon_mask=fixed_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_fixed_tendon_stiffness_index(
             stiffness=stiffness, fixed_tendon_ids=fixed_tendon_ids, env_ids=env_ids, full_data=True
@@ -2906,8 +2907,8 @@ def set_fixed_tendon_damping_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        fixed_tendon_ids = self._resolve_fixed_tendon_ids(fixed_tendon_mask=fixed_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_fixed_tendon_damping_index(
             damping=damping, fixed_tendon_ids=fixed_tendon_ids, env_ids=env_ids, full_data=True
@@ -3010,8 +3011,8 @@ def set_fixed_tendon_limit_stiffness_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        fixed_tendon_ids = self._resolve_fixed_tendon_ids(fixed_tendon_mask=fixed_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_fixed_tendon_limit_stiffness_index(
             limit_stiffness=limit_stiffness, fixed_tendon_ids=fixed_tendon_ids, env_ids=env_ids, full_data=True
@@ -3088,8 +3089,8 @@ def set_fixed_tendon_position_limit_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        fixed_tendon_ids = self._resolve_fixed_tendon_ids(fixed_tendon_mask=fixed_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_fixed_tendon_position_limit_index(
             limit=limit, fixed_tendon_ids=fixed_tendon_ids, env_ids=env_ids, full_data=True
@@ -3192,8 +3193,8 @@ def set_fixed_tendon_rest_length_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        fixed_tendon_ids = self._resolve_fixed_tendon_ids(fixed_tendon_mask=fixed_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_fixed_tendon_rest_length_index(
             rest_length=rest_length, fixed_tendon_ids=fixed_tendon_ids, env_ids=env_ids, full_data=True
@@ -3343,8 +3344,8 @@ def set_fixed_tendon_position_target_mask(
         """
         self.set_fixed_tendon_position_target_index(
             target=target,
-            fixed_tendon_ids=self._resolve_fixed_tendon_mask(fixed_tendon_mask),
-            env_ids=self._resolve_env_mask(env_mask),
+            fixed_tendon_ids=self._resolve_fixed_tendon_ids(fixed_tendon_mask=fixed_tendon_mask),
+            env_ids=self._resolve_env_ids(env_mask=env_mask),
             full_data=True,
         )
 
@@ -3374,8 +3375,8 @@ def set_fixed_tendon_offset_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        fixed_tendon_ids = self._resolve_fixed_tendon_mask(fixed_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        fixed_tendon_ids = self._resolve_fixed_tendon_ids(fixed_tendon_mask=fixed_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_fixed_tendon_offset_index(
             offset=offset, fixed_tendon_ids=fixed_tendon_ids, env_ids=env_ids, full_data=True
@@ -3430,7 +3431,7 @@ def write_fixed_tendon_properties_to_sim_mask(
         only the selected cached values before this method pushes the complete rows.
 
         .. tip::
-            For maximum performance we recommend using the mask method. This is because in PhysX, the tensor API
+            For maximum performance we recommend using the index method. This is because in PhysX, the tensor API
             is only supporting indexing, hence masks need to be converted to indices.
 
         Args:
@@ -3439,7 +3440,7 @@ def write_fixed_tendon_properties_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.write_fixed_tendon_properties_to_sim_index(env_ids=env_ids)
 
     def set_spatial_tendon_stiffness_index(
@@ -3539,8 +3540,8 @@ def set_spatial_tendon_stiffness_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        spatial_tendon_ids = self._resolve_spatial_tendon_mask(spatial_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        spatial_tendon_ids = self._resolve_spatial_tendon_ids(spatial_tendon_mask=spatial_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_spatial_tendon_stiffness_index(
             stiffness=stiffness, spatial_tendon_ids=spatial_tendon_ids, env_ids=env_ids, full_data=True
@@ -3639,8 +3640,8 @@ def set_spatial_tendon_damping_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        spatial_tendon_ids = self._resolve_spatial_tendon_mask(spatial_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        spatial_tendon_ids = self._resolve_spatial_tendon_ids(spatial_tendon_mask=spatial_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_spatial_tendon_damping_index(
             damping=damping, spatial_tendon_ids=spatial_tendon_ids, env_ids=env_ids, full_data=True
@@ -3744,8 +3745,8 @@ def set_spatial_tendon_limit_stiffness_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        spatial_tendon_ids = self._resolve_spatial_tendon_mask(spatial_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        spatial_tendon_ids = self._resolve_spatial_tendon_ids(spatial_tendon_mask=spatial_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_spatial_tendon_limit_stiffness_index(
             limit_stiffness=limit_stiffness, spatial_tendon_ids=spatial_tendon_ids, env_ids=env_ids, full_data=True
@@ -3844,8 +3845,8 @@ def set_spatial_tendon_offset_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
-        spatial_tendon_ids = self._resolve_spatial_tendon_mask(spatial_tendon_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        spatial_tendon_ids = self._resolve_spatial_tendon_ids(spatial_tendon_mask=spatial_tendon_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_spatial_tendon_offset_index(
             offset=offset, spatial_tendon_ids=spatial_tendon_ids, env_ids=env_ids, full_data=True
@@ -3898,7 +3899,7 @@ def write_spatial_tendon_properties_to_sim_mask(
         this method pushes the complete rows.
 
         .. tip::
-            For maximum performance we recommend using the mask method. This is because in PhysX, the tensor API
+            For maximum performance we recommend using the index method. This is because in PhysX, the tensor API
             is only supporting indexing, hence masks need to be converted to indices.
 
         Args:
@@ -3907,7 +3908,7 @@ def write_spatial_tendon_properties_to_sim_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        env_ids = self._resolve_env_mask(env_mask)
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         # Write spatial tendon properties to the simulation.
         self.write_spatial_tendon_properties_to_sim_index(env_ids=env_ids)
 
@@ -4463,62 +4464,23 @@ def _cpu_env_ids_view(self, count: int) -> wp.array:
             )
         return self._cpu_env_ids_views[count]
 
-    def _resolve_env_mask(self, env_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """
-        Resolve environment mask to a torch tensor.
-
-        Args:
-            env_mask: Environment mask. If None, then all indices are used.
-
-        Returns:
-            A torch tensor of environment indices.
-        """
-        # resolve masks
-        if env_mask is not None:
-            if isinstance(env_mask, wp.array):
-                env_mask = wp.to_torch(env_mask)
-            env_ids = torch.nonzero(env_mask)[:, 0]
-        else:
-            env_ids = self._ALL_INDICES
-        return env_ids
-
-    def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
+    def _resolve_env_ids(
+        self, env_ids: Sequence[int] | torch.Tensor | wp.array | None = None, env_mask: wp.array | None = None
+    ) -> wp.array | torch.Tensor:
         """Resolve environment indices.
 
         Args:
             env_ids: Environment indices. If None, then all indices are used.
+            env_mask: Boolean mask; takes precedence over ``env_ids``.
 
         Returns:
             Environment indices.
         """
-        if env_ids is None or (isinstance(env_ids, slice) and env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        return env_ids
-
-    def _resolve_joint_mask(self, joint_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve joint mask to a torch tensor.
-
-        Args:
-            joint_mask: Joint mask. If None, then all indices are used.
+        return resolve_ids(ids=env_ids, mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
 
-        Returns:
-            A torch tensor of joint indices.
-        """
-        if joint_mask is not None:
-            if isinstance(joint_mask, wp.array):
-                joint_mask = wp.to_torch(joint_mask)
-            joint_ids = torch.nonzero(joint_mask)[:, 0]
-        else:
-            joint_ids = self._ALL_JOINT_INDICES
-        return joint_ids
-
-    def _resolve_joint_ids(self, joint_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
+    def _resolve_joint_ids(
+        self, joint_ids: Sequence[int] | torch.Tensor | wp.array | None = None, joint_mask: wp.array | None = None
+    ) -> wp.array | torch.Tensor:
         """Resolve joint indices to a warp array or tensor.
 
         .. note::
@@ -4526,123 +4488,65 @@ def _resolve_joint_ids(self, joint_ids: Sequence[int] | torch.Tensor | wp.array
 
         Args:
             joint_ids: Joint indices. If None, then all indices are used.
+            joint_mask: Boolean mask; takes precedence over ``joint_ids``.
 
         Returns:
             A warp array of joint indices or a tensor of joint indices.
         """
-        if isinstance(joint_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(joint_ids, list):
-            return wp.array(joint_ids, dtype=wp.int32, device=self.device)
-        if (joint_ids is None) or (joint_ids == slice(None)):
-            return self._ALL_JOINT_INDICES
-        return joint_ids
-
-    def _resolve_body_mask(self, body_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve body mask to a torch tensor.
-
-        Args:
-            body_mask: Body mask. If None, then all indices are used.
-
-        Returns:
-            A torch tensor of body indices.
-        """
-        if body_mask is not None:
-            if isinstance(body_mask, wp.array):
-                body_mask = wp.to_torch(body_mask)
-            body_ids = torch.nonzero(body_mask)[:, 0]
-        else:
-            body_ids = self._ALL_BODY_INDICES
-        return body_ids
+        return resolve_ids(ids=joint_ids, mask=joint_mask, all_ids=self._ALL_JOINT_INDICES, device=self.device)
 
-    def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
+    def _resolve_body_ids(
+        self, body_ids: Sequence[int] | torch.Tensor | wp.array | None = None, body_mask: wp.array | None = None
+    ) -> wp.array | torch.Tensor:
         """Resolve body indices to a warp array or tensor.
 
         Args:
             body_ids: Body indices. If None, then all indices are used.
+            body_mask: Boolean mask; takes precedence over ``body_ids``.
 
         Returns:
             A warp array of body indices or a tensor of body indices.
         """
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self.device)
-        if (body_ids is None) or (body_ids == slice(None)):
-            return self._ALL_BODY_INDICES
-        return body_ids
-
-    def _resolve_fixed_tendon_mask(self, fixed_tendon_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve fixed tendon mask to a torch tensor.
-
-        Args:
-            fixed_tendon_mask: Fixed tendon mask. If None, then all indices are used.
-
-        Returns:
-            A torch tensor of fixed tendon indices.
-        """
-        if fixed_tendon_mask is not None:
-            if isinstance(fixed_tendon_mask, wp.array):
-                fixed_tendon_mask = wp.to_torch(fixed_tendon_mask)
-            fixed_tendon_ids = torch.nonzero(fixed_tendon_mask)[:, 0]
-        else:
-            fixed_tendon_ids = self._ALL_FIXED_TENDON_INDICES
-        return fixed_tendon_ids
+        return resolve_ids(ids=body_ids, mask=body_mask, all_ids=self._ALL_BODY_INDICES, device=self.device)
 
     def _resolve_fixed_tendon_ids(
-        self, tendon_ids: Sequence[int] | torch.Tensor | wp.array | None
+        self,
+        tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
+        fixed_tendon_mask: wp.array | None = None,
     ) -> wp.array | torch.Tensor:
         """Resolve tendon indices to a warp array or tensor.
 
         Args:
             tendon_ids: Tendon indices. If None, then all indices are used.
+            fixed_tendon_mask: Boolean mask; takes precedence over ``tendon_ids``.
 
         Returns:
             A warp array of tendon indices or a tensor of tendon indices.
         """
-        if isinstance(tendon_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(tendon_ids, list):
-            return wp.array(tendon_ids, dtype=wp.int32, device=self.device)
-        if (tendon_ids is None) or (tendon_ids == slice(None)):
-            return self._ALL_FIXED_TENDON_INDICES
-        return tendon_ids
-
-    def _resolve_spatial_tendon_mask(self, spatial_tendon_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve spatial tendon mask to a torch tensor.
-
-        Args:
-            spatial_tendon_mask: Spatial tendon mask. If None, then all indices are used.
-
-        Returns:
-            A torch tensor of spatial tendon indices.
-        """
-        if spatial_tendon_mask is not None:
-            if isinstance(spatial_tendon_mask, wp.array):
-                spatial_tendon_mask = wp.to_torch(spatial_tendon_mask)
-            spatial_tendon_ids = torch.nonzero(spatial_tendon_mask)[:, 0]
-        else:
-            spatial_tendon_ids = self._ALL_SPATIAL_TENDON_INDICES
-        return spatial_tendon_ids
+        return resolve_ids(
+            ids=tendon_ids, mask=fixed_tendon_mask, all_ids=self._ALL_FIXED_TENDON_INDICES, device=self.device
+        )
 
     def _resolve_spatial_tendon_ids(
-        self, spatial_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None
+        self,
+        spatial_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
+        spatial_tendon_mask: wp.array | None = None,
     ) -> wp.array | torch.Tensor:
         """Resolve spatial tendon indices to a warp array or tensor.
 
         Args:
             spatial_tendon_ids: Spatial tendon indices. If None, then all indices are used.
+            spatial_tendon_mask: Boolean mask; takes precedence over ``spatial_tendon_ids``.
 
         Returns:
             A warp array of spatial tendon indices or a tensor of spatial tendon indices.
         """
-        if isinstance(spatial_tendon_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(spatial_tendon_ids, list):
-            return wp.array(spatial_tendon_ids, dtype=wp.int32, device=self.device)
-        if (spatial_tendon_ids is None) or (spatial_tendon_ids == slice(None)):
-            return self._ALL_SPATIAL_TENDON_INDICES
-        return spatial_tendon_ids
+        return resolve_ids(
+            ids=spatial_tendon_ids,
+            mask=spatial_tendon_mask,
+            all_ids=self._ALL_SPATIAL_TENDON_INDICES,
+            device=self.device,
+        )
 
     """
     Deprecated methods.
diff --git a/source/isaaclab_physx/isaaclab_physx/assets/deformable_object/deformable_object.py b/source/isaaclab_physx/isaaclab_physx/assets/deformable_object/deformable_object.py
index 019d50bdb1a8..d8dc3d9e7bc3 100644
--- a/source/isaaclab_physx/isaaclab_physx/assets/deformable_object/deformable_object.py
+++ b/source/isaaclab_physx/isaaclab_physx/assets/deformable_object/deformable_object.py
@@ -21,6 +21,7 @@
 from isaaclab.assets.asset_base import AssetBase
 from isaaclab.markers import VisualizationMarkers
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_ids
 
 from .deformable_object_data import DeformableObjectData
 from .kernels import (
@@ -218,10 +219,7 @@ def write_nodal_state_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 6).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_state_to_sim_index(nodal_state, env_ids=env_ids, full_data=True)
 
     def write_nodal_pos_to_sim_index(
@@ -288,10 +286,7 @@ def write_nodal_pos_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 3).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_pos_to_sim_index(nodal_pos, env_ids=env_ids, full_data=True)
 
     def write_nodal_velocity_to_sim_index(
@@ -359,10 +354,7 @@ def write_nodal_velocity_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 3).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_velocity_to_sim_index(nodal_vel, env_ids=env_ids, full_data=True)
 
     def write_nodal_kinematic_target_to_sim_index(
@@ -438,10 +430,7 @@ def write_nodal_kinematic_target_to_sim_mask(
                 Shape is (num_instances, max_sim_vertices_per_body, 4).
             env_mask: Environment mask. If None, then all indices are used.
         """
-        if env_mask is not None:
-            env_ids = wp.nonzero(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = resolve_ids(mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
         self.write_nodal_kinematic_target_to_sim_index(targets, env_ids=env_ids, full_data=True)
 
     """
@@ -566,17 +555,7 @@ def _resolve_env_ids(self, env_ids):
         Returns:
             A warp array of environment indices.
         """
-        if (env_ids is None) or (env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, torch.Tensor):
-            if env_ids.dtype == torch.int64:
-                env_ids = env_ids.to(torch.int32)
-            return wp.from_torch(env_ids, dtype=wp.int32)
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        return env_ids
+        return resolve_ids(ids=env_ids, all_ids=self._ALL_INDICES, device=self.device, dtype=wp.int32)
 
     def _initialize_impl(self):
         # obtain global simulation view
diff --git a/source/isaaclab_physx/isaaclab_physx/assets/rigid_object/rigid_object.py b/source/isaaclab_physx/isaaclab_physx/assets/rigid_object/rigid_object.py
index 47c7240c510e..48d1345349ea 100644
--- a/source/isaaclab_physx/isaaclab_physx/assets/rigid_object/rigid_object.py
+++ b/source/isaaclab_physx/isaaclab_physx/assets/rigid_object/rigid_object.py
@@ -19,6 +19,7 @@
 from isaaclab.assets.rigid_object.base_rigid_object import BaseRigidObject
 from isaaclab.sim.utils.queries import path_expr_to_glob, resolve_matching_prims_from_source
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_ids
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_physx.assets import kernels as shared_kernels
@@ -397,10 +398,7 @@ def write_root_link_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.write_root_link_pose_to_sim_index(
             root_pose=root_pose, env_ids=env_ids, full_data=True, skip_forward=skip_forward
         )
@@ -491,10 +489,7 @@ def write_root_com_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.write_root_com_pose_to_sim_index(
             root_pose=root_pose, env_ids=env_ids, full_data=True, skip_forward=skip_forward
         )
@@ -593,10 +588,7 @@ def write_root_com_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.write_root_com_velocity_to_sim_index(
             root_velocity=root_velocity, env_ids=env_ids, full_data=True, skip_forward=skip_forward
         )
@@ -699,10 +691,7 @@ def write_root_link_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.write_root_link_velocity_to_sim_index(
             root_velocity=root_velocity, env_ids=env_ids, full_data=True, skip_forward=skip_forward
         )
@@ -793,14 +782,8 @@ def set_masses_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_masses_index(masses=masses, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -885,14 +868,8 @@ def set_coms_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_coms_index(coms=coms, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -980,14 +957,8 @@ def set_inertias_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_inertias_index(inertias=inertias, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -1068,40 +1039,6 @@ def _process_cfg(self) -> None:
         self._data.default_root_pose = wp.array(default_root_pose, dtype=wp.transformf, device=self.device)
         self._data.default_root_vel = wp.array(default_root_vel, dtype=wp.spatial_vectorf, device=self.device)
 
-    def _resolve_env_mask(self, env_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve environment mask to a torch tensor.
-
-        Args:
-            env_mask: Environment mask. If None, then all indices are used.
-
-        Returns:
-            A torch tensor of environment indices.
-        """
-        if env_mask is not None:
-            if isinstance(env_mask, wp.array):
-                env_mask = wp.to_torch(env_mask)
-            env_ids = torch.nonzero(env_mask)[:, 0]
-        else:
-            env_ids = self._ALL_INDICES
-        return env_ids
-
-    def _resolve_body_mask(self, body_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve body mask to a torch tensor.
-
-        Args:
-            body_mask: Body mask. If None, then all indices are used.
-
-        Returns:
-            A torch tensor of body indices.
-        """
-        if body_mask is not None:
-            if isinstance(body_mask, wp.array):
-                body_mask = wp.to_torch(body_mask)
-            body_ids = torch.nonzero(body_mask)[:, 0]
-        else:
-            body_ids = self._ALL_BODY_INDICES
-        return body_ids
-
     def _get_cpu_env_ids(self, env_ids: wp.array | torch.Tensor, sim_env_ids: wp.array | None = None) -> wp.array:
         """Get CPU environment indices. Uses pre-allocated pinned buffer for full-index case.
 
@@ -1164,39 +1101,33 @@ def _sim_env_ids_view(self, count: int) -> wp.array:
             )
         return self._sim_env_ids_views[count]
 
-    def _resolve_env_ids(self, env_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
+    def _resolve_env_ids(
+        self, env_ids: Sequence[int] | torch.Tensor | wp.array | None = None, env_mask: wp.array | None = None
+    ) -> wp.array | torch.Tensor:
         """Resolve environment indices to a warp array or tensor.
 
         Args:
             env_ids: Environment indices. If None, then all indices are used.
+            env_mask: Boolean mask; takes precedence over ``env_ids``.
 
         Returns:
             A warp array of environment indices or a tensor of environment indices.
         """
-        if (env_ids is None) or (env_ids == slice(None)):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        return env_ids
-
-    def _resolve_body_ids(self, body_ids: Sequence[int] | torch.Tensor | wp.array | None) -> wp.array | torch.Tensor:
+        return resolve_ids(ids=env_ids, mask=env_mask, all_ids=self._ALL_INDICES, device=self.device)
+
+    def _resolve_body_ids(
+        self, body_ids: Sequence[int] | torch.Tensor | wp.array | None = None, body_mask: wp.array | None = None
+    ) -> wp.array | torch.Tensor:
         """Resolve body indices to a warp array or tensor.
 
         Args:
             body_ids: Body indices. If None, then all indices are used.
+            body_mask: Boolean mask; takes precedence over ``body_ids``.
 
         Returns:
             A warp array of body indices or a tensor of body indices.
         """
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self.device)
-        if (body_ids is None) or (body_ids == slice(None)):
-            return self._ALL_BODY_INDICES
-        return body_ids
+        return resolve_ids(ids=body_ids, mask=body_mask, all_ids=self._ALL_BODY_INDICES, device=self.device)
 
     """
     Internal simulation callbacks.
diff --git a/source/isaaclab_physx/isaaclab_physx/assets/rigid_object_collection/rigid_object_collection.py b/source/isaaclab_physx/isaaclab_physx/assets/rigid_object_collection/rigid_object_collection.py
index 47d5e1cb460b..e79295d59f04 100644
--- a/source/isaaclab_physx/isaaclab_physx/assets/rigid_object_collection/rigid_object_collection.py
+++ b/source/isaaclab_physx/isaaclab_physx/assets/rigid_object_collection/rigid_object_collection.py
@@ -22,6 +22,7 @@
 from isaaclab.assets.rigid_object_collection.base_rigid_object_collection import BaseRigidObjectCollection
 from isaaclab.utils import clone, validate
 from isaaclab.utils.warp import ProxyArray
+from isaaclab.utils.warp.utils import resolve_ids
 from isaaclab.utils.wrench_composer import WrenchComposer
 
 from isaaclab_physx.assets import kernels as shared_kernels
@@ -307,14 +308,8 @@ def write_body_pose_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         self.write_body_link_pose_to_sim_index(
             body_poses=body_poses, env_ids=env_ids, body_ids=body_ids, full_data=True, skip_forward=skip_forward
         )
@@ -391,14 +386,8 @@ def write_body_velocity_to_sim_mask(
             skip_forward: Whether to skip invalidating cached data after the write. When True, the caller
                 must invalidate stale cached data before reading it back. Defaults to False.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         self.write_body_com_velocity_to_sim_index(
             body_velocities=body_velocities,
             env_ids=env_ids,
@@ -509,10 +498,7 @@ def write_body_link_pose_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
             body_ids: Deprecated, use :attr:`body_mask` instead. Body indices. Defaults to None.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         body_ids = self._resolve_mask_writer_body_ids(body_mask, body_ids)
         self.write_body_link_pose_to_sim_index(
             body_poses=body_poses, env_ids=env_ids, body_ids=body_ids, full_data=True, skip_forward=skip_forward
@@ -624,10 +610,7 @@ def write_body_com_pose_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
             body_ids: Deprecated, use :attr:`body_mask` instead. Body indices. Defaults to None.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         body_ids = self._resolve_mask_writer_body_ids(body_mask, body_ids)
         self.write_body_com_pose_to_sim_index(
             body_poses=body_poses, env_ids=env_ids, body_ids=body_ids, full_data=True, skip_forward=skip_forward
@@ -744,10 +727,7 @@ def write_body_com_velocity_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
             body_ids: Deprecated, use :attr:`body_mask` instead. Body indices. Defaults to None.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         body_ids = self._resolve_mask_writer_body_ids(body_mask, body_ids)
         self.write_body_com_velocity_to_sim_index(
             body_velocities=body_velocities,
@@ -871,10 +851,7 @@ def write_body_link_velocity_to_sim_mask(
                 must invalidate stale cached data before reading it back. Defaults to False.
             body_ids: Deprecated, use :attr:`body_mask` instead. Body indices. Defaults to None.
         """
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         body_ids = self._resolve_mask_writer_body_ids(body_mask, body_ids)
         self.write_body_link_velocity_to_sim_index(
             body_velocities=body_velocities,
@@ -968,14 +945,8 @@ def set_masses_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_masses_index(masses=masses, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -1062,14 +1033,8 @@ def set_coms_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_coms_index(coms=coms, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -1157,14 +1122,8 @@ def set_inertias_mask(
             env_mask: Environment mask. If None, then all the instances are updated. Shape is (num_instances,).
         """
         # Resolve masks.
-        if env_mask is not None:
-            env_ids = self._resolve_env_mask(env_mask)
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        if body_mask is not None:
-            body_ids = self._resolve_body_mask(body_mask)
-        else:
-            body_ids = self._ALL_BODY_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
+        body_ids = self._resolve_body_ids(body_mask=body_mask)
         # Set full data to True to ensure the right code path is taken inside the kernel.
         self.set_inertias_index(inertias=inertias, body_ids=body_ids, env_ids=env_ids, full_data=True)
 
@@ -1311,46 +1270,20 @@ def reshape_data_to_view_3d(
     Internal helper.
     """
 
-    def _resolve_env_ids(self, env_ids) -> wp.array | torch.Tensor:
+    def _resolve_env_ids(self, env_ids=None, env_mask: wp.array | None = None) -> wp.array | torch.Tensor:
         """Resolve environment indices."""
-        if (env_ids is None) or (env_ids == slice(None)):
-            return self._ALL_ENV_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_ENV_INDICES)[env_ids])
-        if isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self.device)
-        return env_ids
-
-    def _resolve_body_ids(self, body_ids) -> wp.array | torch.Tensor:
-        """Resolve body indices."""
-        if isinstance(body_ids, ProxyArray):
-            raise TypeError("ProxyArray is output-only; pass .warp or .torch explicitly.")
-        if isinstance(body_ids, list):
-            return wp.array(body_ids, dtype=wp.int32, device=self.device)
-        if body_ids is None or (body_ids == slice(None)):
-            return self._ALL_BODY_INDICES
-        if isinstance(body_ids, slice):
-            return wp.from_torch(
-                torch.arange(self.num_bodies, dtype=torch.int32, device=self.device)[body_ids], dtype=wp.int32
-            )
-        return body_ids
+        return resolve_ids(ids=env_ids, mask=env_mask, all_ids=self._ALL_ENV_INDICES, device=self.device)
 
-    def _resolve_env_mask(self, env_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve environment mask to indices via torch.nonzero."""
-        if env_mask is not None:
-            if isinstance(env_mask, wp.array):
-                env_mask = wp.to_torch(env_mask)
-            env_ids = torch.nonzero(env_mask)[:, 0]
-        else:
-            env_ids = self._ALL_ENV_INDICES
-        return env_ids
+    def _resolve_body_ids(self, body_ids=None, body_mask: wp.array | None = None) -> wp.array | torch.Tensor:
+        """Resolve body indices."""
+        return resolve_ids(ids=body_ids, mask=body_mask, all_ids=self._ALL_BODY_INDICES, device=self.device)
 
     def _resolve_mask_writer_body_ids(
         self, body_mask: wp.array | None, body_ids: Sequence[int] | torch.Tensor | wp.array | slice | None
     ) -> Sequence[int] | torch.Tensor | wp.array | slice:
         """Resolve the bodies of a mask writer, accepting the deprecated ``body_ids`` in place of ``body_mask``."""
         if body_ids is None:
-            return self._resolve_body_mask(body_mask)
+            return self._resolve_body_ids(body_mask=body_mask)
         if body_mask is not None:
             raise ValueError("Pass either 'body_mask' or the deprecated 'body_ids', not both.")
         warnings.warn(
@@ -1361,16 +1294,6 @@ def _resolve_mask_writer_body_ids(
         )
         return body_ids
 
-    def _resolve_body_mask(self, body_mask: wp.array | None) -> torch.Tensor | wp.array:
-        """Resolve body mask to indices via torch.nonzero."""
-        if body_mask is not None:
-            if isinstance(body_mask, wp.array):
-                body_mask = wp.to_torch(body_mask)
-            body_ids = torch.nonzero(body_mask)[:, 0]
-        else:
-            body_ids = self._ALL_BODY_INDICES
-        return body_ids
-
     def _initialize_impl(self):
         # clear body names list to prevent double counting on re-initialization
         self._body_names_list.clear()
diff --git a/source/isaaclab_physx/isaaclab_physx/assets/surface_gripper/surface_gripper.py b/source/isaaclab_physx/isaaclab_physx/assets/surface_gripper/surface_gripper.py
index e37a30f7a505..a2f5cb930c8f 100644
--- a/source/isaaclab_physx/isaaclab_physx/assets/surface_gripper/surface_gripper.py
+++ b/source/isaaclab_physx/isaaclab_physx/assets/surface_gripper/surface_gripper.py
@@ -16,6 +16,7 @@
 from isaaclab.assets import AssetBase
 from isaaclab.utils import clone
 from isaaclab.utils.version import get_isaac_sim_version, has_kit
+from isaaclab.utils.warp.utils import resolve_ids
 
 if TYPE_CHECKING:
     from isaacsim.robot.surface_gripper import GripperView
@@ -187,10 +188,7 @@ def set_grippers_command_mask(self, states: torch.Tensor | wp.array, env_mask: t
             states: A tensor/array of floats representing the gripper command (full size).
             env_mask: Boolean mask of shape (num_envs,). Defaults to None (all environments).
         """
-        if env_mask is not None:
-            env_ids = wp.from_torch(torch.argwhere(env_mask).view(-1).to(torch.int32), dtype=wp.int32)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.set_grippers_command_index(states, env_ids, full_data=True)
 
     def set_grippers_command(self, states: torch.Tensor, indices: torch.Tensor | None = None) -> None:
@@ -274,10 +272,7 @@ def update_gripper_properties_mask(
             retry_interval: The retry interval. Shape (num_envs,).
             env_mask: Boolean mask of shape (num_envs,). Defaults to None (all environments).
         """
-        if env_mask is not None:
-            env_ids = wp.from_torch(torch.argwhere(env_mask).view(-1).to(torch.int32), dtype=wp.int32)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.update_gripper_properties_index(
             max_grip_distance=max_grip_distance,
             coaxial_force_limit=coaxial_force_limit,
@@ -407,10 +402,7 @@ def reset_mask(self, env_mask: torch.Tensor | None = None) -> None:
         Args:
             env_mask: Boolean mask of shape (num_envs,). Defaults to None (all environments).
         """
-        if env_mask is not None:
-            env_ids = wp.from_torch(torch.argwhere(env_mask).view(-1).to(torch.int32), dtype=wp.int32)
-        else:
-            env_ids = self._ALL_INDICES
+        env_ids = self._resolve_env_ids(env_mask=env_mask)
         self.reset_index(env_ids)
 
     def reset(self, indices: torch.Tensor | None = None) -> None:
@@ -552,24 +544,17 @@ def _process_cfg(self) -> None:
     Helper functions.
     """
 
-    def _resolve_env_ids(self, env_ids) -> wp.array:
+    def _resolve_env_ids(self, env_ids=None, env_mask: wp.array | torch.Tensor | None = None) -> wp.array:
         """Resolve environment indices to a warp array.
 
         Args:
             env_ids: Environment indices. Can be None, a slice, a list, or a torch.Tensor.
+            env_mask: Boolean mask; takes precedence over ``env_ids``.
 
         Returns:
             A warp array of int32 indices.
         """
-        if env_ids is None or env_ids == slice(None):
-            return self._ALL_INDICES
-        if isinstance(env_ids, slice):
-            return wp.from_torch(wp.to_torch(self._ALL_INDICES)[env_ids])
-        elif isinstance(env_ids, list):
-            return wp.array(env_ids, dtype=wp.int32, device=self._device)
-        elif isinstance(env_ids, torch.Tensor):
-            return wp.from_torch(env_ids.to(torch.int32).contiguous(), dtype=wp.int32)
-        return env_ids
+        return resolve_ids(ids=env_ids, mask=env_mask, all_ids=self._ALL_INDICES, device=self._device, dtype=wp.int32)
 
     def parse_gripper_parameter(
         self, cfg_value: float | int | tuple | None, default_value: float | int | tuple | None, ndim: int = 0
diff --git a/source/isaaclab_physx/test/assets/test_deformable_object.py b/source/isaaclab_physx/test/assets/test_deformable_object.py
index cfd389fa99ef..4eeb4c246f8c 100644
--- a/source/isaaclab_physx/test/assets/test_deformable_object.py
+++ b/source/isaaclab_physx/test/assets/test_deformable_object.py
@@ -244,6 +244,22 @@ def test_deformable_nodal_state_writes(deformable_scene: _DeformableScene) -> No
     torch.testing.assert_close(raw_nodal_pos.reshape(nodal_pos.shape), nodal_pos)
 
 
+@pytest.mark.isaacsim_ci
+def test_deformable_nodal_state_mask_writes(deformable_scene: _DeformableScene) -> None:
+    """Mask writes take full-size data and reach only the environments the mask selects."""
+    scene = deformable_scene
+    device = scene.device
+    env_mask = wp.array([False, True], dtype=wp.bool, device=device)
+    for deformable in (scene.volume, scene.surface):
+        initial_state = deformable.data.nodal_state_w.torch.clone()
+        state = initial_state.clone()
+        state[:, 0, :3] += torch.tensor([0.01, 0.02, 0.03], device=device)
+        state[:, 0, 3] = 0.25
+        deformable.write_nodal_state_to_sim_mask(state, env_mask=env_mask)
+        expected = torch.cat((initial_state[:1], state[1:]))
+        torch.testing.assert_close(deformable.data.nodal_state_w.torch, expected)
+
+
 @pytest.mark.isaacsim_ci
 def test_volume_kinematic_targets_hold_selected_nodes(deformable_scene: _DeformableScene) -> None:
     """Kinematic targets of environment 0 hold its nodes while environment 1 keeps moving freely."""
diff --git a/source/isaaclab_physx/test/sensors/test_frame_transformer.py b/source/isaaclab_physx/test/sensors/test_frame_transformer.py
index 7ba9a23d3de4..50e52bfbc646 100644
--- a/source/isaaclab_physx/test/sensors/test_frame_transformer.py
+++ b/source/isaaclab_physx/test/sensors/test_frame_transformer.py
@@ -655,6 +655,8 @@ def _make_frame_transformer(use_recorded_launch: bool = True):
     sensor.cfg = SimpleNamespace(prim_path="/World/Source")
     sensor._device = device
     sensor._num_envs = 1
+    sensor._ALL_ENV_MASK = wp.ones(1, dtype=wp.bool, device=device)
+    sensor._reset_mask = wp.zeros(1, dtype=wp.bool, device=device)
     sensor._num_target_frames = 1
     sensor._frame_physx_view = transform_view
     sensor._backend_manager = SimpleNamespace(update_kinematics=lambda: None)
diff --git a/source/isaaclab_physx/test/sensors/test_imu_pva_recorded_launch.py b/source/isaaclab_physx/test/sensors/test_imu_pva_recorded_launch.py
index ea2a1b6df989..80c2956113de 100644
--- a/source/isaaclab_physx/test/sensors/test_imu_pva_recorded_launch.py
+++ b/source/isaaclab_physx/test/sensors/test_imu_pva_recorded_launch.py
@@ -122,6 +122,8 @@ def _make_sensor(sensor_type: str, use_recorded_launch: bool = True):
     sensor._device = device
     sensor._backend_manager = SimpleNamespace(update_kinematics=lambda: None)
     sensor._num_envs = 2
+    sensor._ALL_ENV_MASK = wp.ones(2, dtype=wp.bool, device=device)
+    sensor._reset_mask = wp.zeros(2, dtype=wp.bool, device=device)
     sensor._view = rigid_view
     sensor._offset_pos_b = wp.zeros(2, dtype=wp.vec3f, device=device)
     sensor._offset_quat_b = wp.array(