Fixes joint out of position limits terminations (#2442)

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This PR fixes shape‑handling bugs in the termination helpers
**`joint_pos_out_of_limit`** and **`joint_pos_out_of_manual_limit`**:

* **Root cause** – both functions reduced across joints with
`torch.any(dim=1)` **before** slicing with `asset_cfg.joint_ids`,
leaving a 1‑D tensor and triggering an `IndexError: too many indices`.
* **Fix** – construct a single `violations` mask, optionally slice
joints, **then** reduce with `torch.any(dim=1)`.
This preserves correct shapes (`[num_envs]`) and works for any
joint‑selection type (`None`, `slice`, list, or tensor).
* **Additional improvements**

* Made `asset_cfg` immutable by avoiding in‑place modification of
`joint_ids`.
  * Added docstring details and harmonised logic between both helpers.

No new dependencies were introduced.

Fixes #2441

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---------

Signed-off-by: Giulio Romualdi <giulio.romualdi@gmail.com>
Co-authored-by: Kelly Guo <kellyg@nvidia.com>

Author: GiulioRomualdi

source/isaaclab/isaaclab/envs/mdp/terminations.py

@@ -81,10 +81,13 @@ def joint_pos_out_of_limit(env: ManagerBasedRLEnv, asset_cfg: SceneEntityCfg = S
     """Terminate when the asset's joint positions are outside of the soft joint limits."""
     # extract the used quantities (to enable type-hinting)
     asset: Articulation = env.scene[asset_cfg.name]
-    # compute any violations
-    out_of_upper_limits = torch.any(asset.data.joint_pos > asset.data.soft_joint_pos_limits[..., 1], dim=1)
-    out_of_lower_limits = torch.any(asset.data.joint_pos < asset.data.soft_joint_pos_limits[..., 0], dim=1)
-    return torch.logical_or(out_of_upper_limits[:, asset_cfg.joint_ids], out_of_lower_limits[:, asset_cfg.joint_ids])
+    if asset_cfg.joint_ids is None:
+        asset_cfg.joint_ids = slice(None)
+
+    limits = asset.data.soft_joint_pos_limits[:, asset_cfg.joint_ids]
+    out_of_upper_limits = torch.any(asset.data.joint_pos[:, asset_cfg.joint_ids] > limits[..., 1], dim=1)
+    out_of_lower_limits = torch.any(asset.data.joint_pos[:, asset_cfg.joint_ids] < limits[..., 0], dim=1)
+    return torch.logical_or(out_of_upper_limits, out_of_lower_limits)
 
 
 def joint_pos_out_of_manual_limit(