Updated based on feedback

Author: AntoineRichard

source/isaaclab/isaaclab/envs/mdp/actions/joint_actions.py

@@ -138,8 +138,8 @@ def IO_descriptor(self) -> GenericActionIODescriptor:
         else:
             self._IO_descriptor.offset = self._offset
         #FIXME: This is not correct. Add list support.
-        if self.cfg.clip is not None: 
-            self._IO_descriptor.clip = self._clip
+        if isinstance(self._clip, torch.Tensor):
+            self._IO_descriptor.clip = self._clip[0].detach().cpu().numpy().tolist()
         else:
             self._IO_descriptor.clip = None
         return self._IO_descriptor

source/isaaclab/isaaclab/envs/mdp/observations.py

@@ -30,6 +30,8 @@
     record_dtype,
     record_joint_names,
     record_shape,
+    record_joint_pos_offsets,
+    record_joint_vel_offsets,
 )
 
 """
@@ -198,7 +200,7 @@ def joint_pos(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("
 
 
 @generic_io_descriptor(
-    observation_type="JointState", on_inspect=[record_joint_names, record_dtype, record_shape], units="rad"
+    observation_type="JointState", on_inspect=[record_joint_names, record_dtype, record_shape, record_joint_pos_offsets], units="rad"
 )
 def joint_pos_rel(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("robot")) -> torch.Tensor:
     """The joint positions of the asset w.r.t. the default joint positions.
@@ -241,7 +243,7 @@ def joint_vel(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("
 
 
 @generic_io_descriptor(
-    observation_type="JointState", on_inspect=[record_joint_names, record_dtype, record_shape], units="rad/s"
+    observation_type="JointState", on_inspect=[record_joint_names, record_dtype, record_shape, record_joint_vel_offsets], units="rad/s"
 )
 def joint_vel_rel(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("robot")):
     """The joint velocities of the asset w.r.t. the default joint velocities.

source/isaaclab/isaaclab/envs/utils/io_descriptors.py

@@ -192,10 +192,39 @@ def record_joint_names(output: torch.Tensor, descriptor: GenericIODescriptor, **
         joint_ids = list(range(len(asset.joint_names)))
     descriptor.joint_names = [asset.joint_names[i] for i in joint_ids]
 
-
 def record_body_names(output: torch.Tensor, descriptor: GenericIODescriptor, **kwargs):
     asset: Articulation = kwargs["env"].scene[kwargs["asset_cfg"].name]
     body_ids = kwargs["asset_cfg"].body_ids
     if body_ids == slice(None, None, None):
         body_ids = list(range(len(asset.body_names)))
     descriptor.body_names = [asset.body_names[i] for i in body_ids]
+
+def record_joint_pos_offsets(output: torch.Tensor, descriptor: GenericIODescriptor, **kwargs):
+    asset: Articulation = kwargs["env"].scene[kwargs["asset_cfg"].name]
+    ids = kwargs["asset_cfg"].joint_ids
+    # Get the offsets of the joints for the first robot in the scene.
+    # This assumes that all robots have the same joint offsets.
+    descriptor.joint_pos_offsets = asset.data.default_joint_pos[:, ids][0]
+
+def record_joint_vel_offsets(output: torch.Tensor, descriptor: GenericIODescriptor, **kwargs):
+    asset: Articulation = kwargs["env"].scene[kwargs["asset_cfg"].name]
+    ids = kwargs["asset_cfg"].joint_ids
+    # Get the offsets of the joints for the first robot in the scene.
+    # This assumes that all robots have the same joint offsets.
+    descriptor.joint_vel_offsets = asset.data.default_joint_vel[:, ids][0]
+
+
+def export_articulations_data(env: ManagerBasedEnv):
+    articulation_joint_data = {}
+    for articulation_name, articulation in env.scene.articulations.items():
+        articulation_joint_data[articulation_name] = {}
+        articulation_joint_data[articulation_name]["joint_names"] = articulation.joint_names
+        articulation_joint_data[articulation_name]["default_joint_pos"] = articulation.data.default_joint_pos[0].detach().cpu().numpy().tolist()
+        articulation_joint_data[articulation_name]["default_joint_vel"] = articulation.data.default_joint_vel[0].detach().cpu().numpy().tolist()
+        articulation_joint_data[articulation_name]["default_joint_pos_limits"] = articulation.data.default_joint_pos_limits[0].detach().cpu().numpy().tolist()
+        articulation_joint_data[articulation_name]["default_joint_damping"] = articulation.data.default_joint_damping[0].detach().cpu().numpy().tolist()
+        articulation_joint_data[articulation_name]["default_joint_stiffness"] = articulation.data.default_joint_stiffness[0].detach().cpu().numpy().tolist()
+        articulation_joint_data[articulation_name]["default_joint_friction"] = articulation.data.default_joint_friction[0].detach().cpu().numpy().tolist()
+        articulation_joint_data[articulation_name]["default_joint_armature"] = articulation.data.default_joint_armature[0].detach().cpu().numpy().tolist()
+    return articulation_joint_data
+    

source/isaaclab/isaaclab/managers/observation_manager.py

@@ -233,9 +233,10 @@ def get_IO_descriptors(self):
             A dictionary with keys as the group names and values as the IO descriptors.
         """
 
-        data = []
+        group_data = {}
 
         for group_name in self._group_obs_term_names:
+            group_data[group_name] = []
             # check ig group name is valid
             if group_name not in self._group_obs_term_names:
                 raise ValueError(
@@ -261,26 +262,27 @@ def get_IO_descriptors(self):
                         if k in ["modifiers", "clip", "scale", "history_length", "flatten_history_dim"]:
                             overloads[k] = v
                     desc.update(overloads)
-                    data.append(desc)
+                    group_data[group_name].append(desc)
                 except Exception as e:
                     print(f"Error getting IO descriptor for term '{term_name}' in group '{group_name}': {e}")
         # Format the data for YAML export
         formatted_data = {}
-        for item in data:
-            name = item.pop("name")
-            formatted_item = {"overloads": {}, "extras": item.pop("extras")}
-            for k, v in item.items():
-                # Check if v is a tuple and convert to list
-                if isinstance(v, tuple):
-                    v = list(v)
-                if k in ["scale", "clip", "history_length", "flatten_history_dim"]:
-                    formatted_item["overloads"][k] = v
-                elif k in ["modifiers", "description", "units"]:
-                    formatted_item["extras"][k] = v
-                else:
-                    formatted_item[k] = v
-            formatted_data[name] = formatted_item
-
+        for group_name, data in group_data.items():
+            formatted_data[group_name] = []
+            for item in data:
+                name = item.pop("name")
+                formatted_item = {"name": name, "overloads": {}, "extras": item.pop("extras")}
+                for k, v in item.items():
+                    # Check if v is a tuple and convert to list
+                    if isinstance(v, tuple):
+                        v = list(v)
+                    if k in ["scale", "clip", "history_length", "flatten_history_dim"]:
+                        formatted_item["overloads"][k] = v
+                    elif k in ["modifiers", "description", "units"]:
+                        formatted_item["extras"][k] = v
+                    else:
+                        formatted_item[k] = v
+                formatted_data[group_name].append(formatted_item)
         return formatted_data
 
     """