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| import numpy as np |
| import torch |
| from typing import Dict, List |
|
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| from robot_joints import JointsAbsPosition |
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|
| def remap_sim_joints_to_policy_joints( |
| sim_joints_state: JointsAbsPosition, policy_joints_config: Dict[str, List[str]] |
| ) -> Dict[str, np.ndarray]: |
| """ |
| Remap the state or actions joints from simulation joint orders to policy joint orders |
| """ |
| data = {} |
| assert isinstance(sim_joints_state, JointsAbsPosition) |
| for group, joints_list in policy_joints_config.items(): |
| data[group] = [] |
| for joint_name in joints_list: |
| if joint_name in sim_joints_state.joints_order_config: |
| joint_index = sim_joints_state.joints_order_config[joint_name] |
| data[group].append(sim_joints_state.joints_pos[:, joint_index]) |
| else: |
| raise ValueError(f"Joint {joint_name} not found in {sim_joints_state.joints_order_config}") |
|
|
| data[group] = np.stack(data[group], axis=1) |
| return data |
|
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|
| def remap_policy_joints_to_sim_joints( |
| policy_joints: Dict[str, np.array], |
| policy_joints_config: Dict[str, List[str]], |
| sim_joints_config: Dict[str, int], |
| device: torch.device, |
| ) -> JointsAbsPosition: |
| """ |
| Remap the actions joints from policy joint orders to simulation joint orders |
| """ |
| |
| policy_joint_shape = None |
| for _, joint_pos in policy_joints.items(): |
| if policy_joint_shape is None: |
| policy_joint_shape = joint_pos.shape |
| else: |
| assert joint_pos.ndim == 3 |
| assert joint_pos.shape[:2] == policy_joint_shape[:2] |
|
|
| assert policy_joint_shape is not None |
| data = torch.zeros([policy_joint_shape[0], policy_joint_shape[1], len(sim_joints_config)], device=device) |
| for joint_name, gr1_index in sim_joints_config.items(): |
| match joint_name.split("_")[0]: |
| case "left": |
| joint_group = "left_arm" |
| case "right": |
| joint_group = "right_arm" |
| case "L": |
| joint_group = "left_hand" |
| case "R": |
| joint_group = "right_hand" |
| case _: |
| continue |
| if joint_name in policy_joints_config[joint_group]: |
| gr00t_index = policy_joints_config[joint_group].index(joint_name) |
| data[..., gr1_index] = torch.from_numpy(policy_joints[f"action.{joint_group}"][..., gr00t_index]).to(device) |
|
|
| sim_joints = JointsAbsPosition(joints_pos=data, joints_order_config=sim_joints_config, device=device) |
| return sim_joints |
|
|
