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42d9709 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import torch
from typing import Dict, List
from robot_joints import JointsAbsPosition
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
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
"""
# assert all values in policy_joint keys are the same shape and save the shape to init data
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
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