feat: add clip range of JointAction

source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/actions_cfg.py

@@ -29,6 +29,8 @@ class JointActionCfg(ActionTermCfg):
     """Scale factor for the action (float or dict of regex expressions). Defaults to 1.0."""
     offset: float | dict[str, float] = 0.0
     """Offset factor for the action (float or dict of regex expressions). Defaults to 0.0."""
+    clip: dict[str, tuple] | None = None
+    """Clip range for the action (dict of regex expressions). Defaults to None."""
     preserve_order: bool = False
     """Whether to preserve the order of the joint names in the action output. Defaults to False."""
 

source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions.py

@@ -50,6 +50,8 @@ class JointAction(ActionTerm):
     """The scaling factor applied to the input action."""
     _offset: torch.Tensor | float
     """The offset applied to the input action."""
+    _clip: dict[str, tuple] | None = None
+    """The clip applied to the input action."""
 
     def __init__(self, cfg: actions_cfg.JointActionCfg, env: ManagerBasedEnv) -> None:
         # initialize the action term
@@ -94,6 +96,12 @@ def __init__(self, cfg: actions_cfg.JointActionCfg, env: ManagerBasedEnv) -> Non
             self._offset[:, index_list] = torch.tensor(value_list, device=self.device)
         else:
             raise ValueError(f"Unsupported offset type: {type(cfg.offset)}. Supported types are float and dict.")
+        # parse clip
+        if cfg.clip is not None:
+            if isinstance(cfg.clip, dict):
+                self._clip = cfg.clip
+            else:
+                raise ValueError(f"Unsupported clip type: {type(cfg.scale)}. Supported types are dict.")
 
     """
     Properties.
@@ -120,6 +128,13 @@ def process_actions(self, actions: torch.Tensor):
         self._raw_actions[:] = actions
         # apply the affine transformations
         self._processed_actions = self._raw_actions * self._scale + self._offset
+        # clip actions
+        if self._clip is not None:
+            # resolve the dictionary config
+            index_list, _, value_list = string_utils.resolve_matching_names_values(self._clip, self._joint_names)
+            for index in range(len(index_list)):
+                min_value, max_value = value_list[index]
+                self._processed_actions[:, index_list[index]].clip_(min_value, max_value)
 
     def reset(self, env_ids: Sequence[int] | None = None) -> None:
         self._raw_actions[env_ids] = 0.0