feat: add clip-cfg to ActionTermCfg && add clip to all mdp/actions

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

@@ -29,8 +29,6 @@ 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/binary_joint_actions.py

@@ -40,9 +40,10 @@ class BinaryJointAction(ActionTerm):
 
     cfg: actions_cfg.BinaryJointActionCfg
     """The configuration of the action term."""
-
     _asset: Articulation
     """The articulation asset on which the action term is applied."""
+    _clip: dict[str, tuple] | None = None
+    """The clip applied to the input action."""
 
     def __init__(self, cfg: actions_cfg.BinaryJointActionCfg, env: ManagerBasedEnv) -> None:
         # initialize the action term
@@ -83,6 +84,13 @@ def __init__(self, cfg: actions_cfg.BinaryJointActionCfg, env: ManagerBasedEnv)
             )
         self._close_command[index_list] = torch.tensor(value_list, device=self.device)
 
+        # 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.clip)}. Supported types are dict.")
+
     """
     Properties.
     """
@@ -115,6 +123,13 @@ def process_actions(self, actions: torch.Tensor):
             binary_mask = actions < 0
         # compute the command
         self._processed_actions = torch.where(binary_mask, self._close_command, self._open_command)
+        # 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

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

@@ -101,7 +101,7 @@ def __init__(self, cfg: actions_cfg.JointActionCfg, env: ManagerBasedEnv) -> Non
             if isinstance(cfg.clip, dict):
                 self._clip = cfg.clip
             else:
-                raise ValueError(f"Unsupported clip type: {type(cfg.scale)}. Supported types are dict.")
+                raise ValueError(f"Unsupported clip type: {type(cfg.clip)}. Supported types are dict.")
 
     """
     Properties.
@@ -134,6 +134,7 @@ def process_actions(self, actions: torch.Tensor):
             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]
+                print(value_list[index])
                 self._processed_actions[:, index_list[index]].clip_(min_value, max_value)
 
     def reset(self, env_ids: Sequence[int] | None = None) -> None:

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

@@ -44,6 +44,8 @@ class JointPositionToLimitsAction(ActionTerm):
     """The articulation asset on which the action term is applied."""
     _scale: torch.Tensor | float
     """The scaling factor applied to the input action."""
+    _clip: dict[str, tuple] | None = None
+    """The clip applied to the input action."""
 
     def __init__(self, cfg: actions_cfg.JointPositionToLimitsActionCfg, env: ManagerBasedEnv):
         # initialize the action term
@@ -76,6 +78,12 @@ def __init__(self, cfg: actions_cfg.JointPositionToLimitsActionCfg, env: Manager
             self._scale[:, index_list] = torch.tensor(value_list, device=self.device)
         else:
             raise ValueError(f"Unsupported scale type: {type(cfg.scale)}. 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.clip)}. Supported types are dict.")
 
     """
     Properties.
@@ -102,6 +110,13 @@ def process_actions(self, actions: torch.Tensor):
         self._raw_actions[:] = actions
         # apply affine transformations
         self._processed_actions = self._raw_actions * self._scale
+        # 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)
         # rescale the position targets if configured
         # this is useful when the input actions are in the range [-1, 1]
         if self.cfg.rescale_to_limits:

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

@@ -11,6 +11,7 @@
 
 import omni.log
 
+import omni.isaac.lab.utils.string as string_utils
 from omni.isaac.lab.assets.articulation import Articulation
 from omni.isaac.lab.managers.action_manager import ActionTerm
 from omni.isaac.lab.utils.math import euler_xyz_from_quat
@@ -59,6 +60,8 @@ class NonHolonomicAction(ActionTerm):
     """The scaling factor applied to the input action. Shape is (1, 2)."""
     _offset: torch.Tensor
     """The offset applied to the input action. Shape is (1, 2)."""
+    _clip: dict[str, tuple] | None = None
+    """The clip applied to the input action."""
 
     def __init__(self, cfg: actions_cfg.NonHolonomicActionCfg, env: ManagerBasedEnv):
         # initialize the action term
@@ -104,6 +107,12 @@ def __init__(self, cfg: actions_cfg.NonHolonomicActionCfg, env: ManagerBasedEnv)
         # save the scale and offset as tensors
         self._scale = torch.tensor(self.cfg.scale, device=self.device).unsqueeze(0)
         self._offset = torch.tensor(self.cfg.offset, device=self.device).unsqueeze(0)
+        # 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.clip)}. Supported types are dict.")
 
     """
     Properties.
@@ -129,6 +138,13 @@ def process_actions(self, actions):
         # store the raw actions
         self._raw_actions[:] = actions
         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 apply_actions(self):
         # obtain current heading

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

@@ -12,6 +12,7 @@
 import omni.log
 
 import omni.isaac.lab.utils.math as math_utils
+import omni.isaac.lab.utils.string as string_utils
 from omni.isaac.lab.assets.articulation import Articulation
 from omni.isaac.lab.controllers.differential_ik import DifferentialIKController
 from omni.isaac.lab.managers.action_manager import ActionTerm
@@ -42,6 +43,8 @@ class DifferentialInverseKinematicsAction(ActionTerm):
     """The articulation asset on which the action term is applied."""
     _scale: torch.Tensor
     """The scaling factor applied to the input action. Shape is (1, action_dim)."""
+    _clip: dict[str, tuple] | None = None
+    """The clip applied to the input action."""
 
     def __init__(self, cfg: actions_cfg.DifferentialInverseKinematicsActionCfg, env: ManagerBasedEnv):
         # initialize the action term
@@ -101,6 +104,13 @@ def __init__(self, cfg: actions_cfg.DifferentialInverseKinematicsActionCfg, env:
         else:
             self._offset_pos, self._offset_rot = None, None
 
+        # 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.clip)}. Supported types are dict.")
+
     """
     Properties.
     """
@@ -125,6 +135,13 @@ def process_actions(self, actions: torch.Tensor):
         # store the raw actions
         self._raw_actions[:] = actions
         self._processed_actions[:] = self.raw_actions * self._scale
+        # 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)
         # obtain quantities from simulation
         ee_pos_curr, ee_quat_curr = self._compute_frame_pose()
         # set command into controller

source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_term_cfg.py

@@ -76,6 +76,9 @@ class for more details.
     debug_vis: bool = False
     """Whether to visualize debug information. Defaults to False."""
 
+    clip: dict[str, tuple] | None = None
+    """Clip range for the action (dict of regex expressions). Defaults to None."""
+
 
 ##
 # Command manager.

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/velocity_env_cfg.py

@@ -109,7 +109,13 @@ class CommandsCfg:
 class ActionsCfg:
     """Action specifications for the MDP."""
 
-    joint_pos = mdp.JointPositionActionCfg(asset_name="robot", joint_names=[".*"], scale=0.5, use_default_offset=True)
+    joint_pos = mdp.JointPositionActionCfg(
+        asset_name="robot",
+        joint_names=[".*"],
+        scale=0.5,
+        use_default_offset=True,
+        clip={".*": (-100.0, 100.0)},  # only for test
+    )
 
 
 @configclass