510 lines
18 KiB
Python
510 lines
18 KiB
Python
from legged_gym import LEGGED_GYM_ROOT_DIR
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from typing import Union, List
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import numpy as np
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import time
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import torch
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import torch as th
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from pathlib import Path
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import rclpy as rp
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from unitree_hg.msg import LowCmd as LowCmdHG, LowState as LowStateHG
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from unitree_go.msg import LowCmd as LowCmdGo, LowState as LowStateGo
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from tf2_ros import TransformException
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from tf2_ros.buffer import Buffer
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from tf2_ros.transform_listener import TransformListener
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from tf2_ros import TransformBroadcaster, TransformStamped
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from common.command_helper_ros import create_damping_cmd, create_zero_cmd, init_cmd_hg, init_cmd_go, MotorMode
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from common.rotation_helper import get_gravity_orientation, transform_imu_data
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from common.remote_controller import RemoteController, KeyMap
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from config import Config
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from common.crc import CRC
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from enum import Enum
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import pinocchio as pin
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from ikctrl import IKCtrl, xyzw2wxyz
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from yourdfpy import URDF
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import math_utils
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import random as rd
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from act_to_dof import ActToDof
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class Mode(Enum):
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wait = 0
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zero_torque = 1
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default_pos = 2
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damping = 3
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policy = 4
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null = 5
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axis_angle_from_quat = math_utils.as_np(math_utils.axis_angle_from_quat)
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quat_conjugate = math_utils.as_np(math_utils.quat_conjugate)
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quat_mul = math_utils.as_np(math_utils.quat_mul)
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quat_rotate = math_utils.as_np(math_utils.quat_rotate)
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quat_rotate_inverse = math_utils.as_np(math_utils.quat_rotate_inverse)
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wrap_to_pi = math_utils.as_np(math_utils.wrap_to_pi)
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combine_frame_transforms = math_utils.as_np(
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math_utils.combine_frame_transforms)
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# Create a mapping tensor
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# mapping_tensor = torch.zeros((len(sim_b_joints), len(sim_a_joints)), device=env.device)
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def body_pose(
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tf_buffer,
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frame: str,
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ref_frame: str = 'pelvis',
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stamp=None,
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rot_type: str = 'axa'):
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""" --> tf does not exist """
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if stamp is None:
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stamp = rp.time.Time()
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try:
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# t = "ref{=pelvis}_from_frame" transform
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t = tf_buffer.lookup_transform(
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ref_frame, # to
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frame, # from
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stamp)
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except TransformException as ex:
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print(f'Could not transform {frame} to {ref_frame}: {ex}')
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raise
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txn = t.transform.translation
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rxn = t.transform.rotation
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xyz = np.array([txn.x, txn.y, txn.z])
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quat_wxyz = np.array([rxn.w, rxn.x, rxn.y, rxn.z])
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xyz = np.array(xyz)
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if rot_type == 'axa':
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axa = axis_angle_from_quat(quat_wxyz)
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axa = wrap_to_pi(axa)
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return (xyz, axa)
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elif rot_type == 'quat':
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return (xyz, quat_wxyz)
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raise ValueError(f"Unknown rot_type: {rot_type}")
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from common.xml_helper import extract_link_data
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def compute_com(tf_buffer, body_frames: List[str]):
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"""compute com of body frames"""
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mass_list = []
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com_list = []
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# bring default values
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com_data = extract_link_data(
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'../../resources/robots/g1_description/g1_29dof_rev_1_0.xml')
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# iterate for frames
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for frame in body_frames:
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try:
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frame_data = com_data[frame]
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except KeyError:
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continue
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try:
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link_pos, link_wxyz = body_pose(tf_buffer,
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frame, rot_type='quat')
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except TransformException:
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continue
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com_pos_b, com_wxyz = frame_data['pos'], frame_data['quat']
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# compute com from world coordinates
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# NOTE 'math_utils' package will be brought from isaaclab
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com_pos = link_pos + quat_rotate(link_wxyz, com_pos_b)
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com_list.append(com_pos)
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# get math
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mass = frame_data['mass']
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mass_list.append(mass)
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com = sum([m * pos for m, pos in zip(mass_list, com_list)]) / sum(mass_list)
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return com
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def index_map(k_to, k_from):
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"""
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Returns an index mapping from k_from to k_to.
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Given k_to=a, k_from=b,
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returns an index map "a_from_b" such that
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array_a[a_from_b] = array_b
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Missing values are set to -1.
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"""
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index_dict = {k: i for i, k in enumerate(k_to)} # O(len(k_from))
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return [index_dict.get(k, -1) for k in k_from] # O(len(k_to))
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class Observation:
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def __init__(self,
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urdf_path: str,
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config,
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tf_buffer: Buffer):
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self.links = list(URDF.load(urdf_path).link_map.keys())
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self.config = config
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self.num_lab_joint = len(config.lab_joint)
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self.tf_buffer = tf_buffer
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self.lab_from_mot = index_map(config.lab_joint,
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config.motor_joint)
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def __call__(self,
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low_state: LowStateHG,
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last_action: np.ndarray,
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hands_command: np.ndarray
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):
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lab_from_mot = self.lab_from_mot
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num_lab_joint = self.num_lab_joint
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# FIXME(ycho): dummy value
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# base_lin_vel = np.zeros(3)
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ang_vel = np.array([low_state.imu_state.gyroscope],
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dtype=np.float32)
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if True:
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# NOTE(ycho): requires running `fake_world_tf_pub.py`.
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world_from_pelvis = self.tf_buffer.lookup_transform(
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'world',
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'pelvis',
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rp.time.Time()
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)
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rxn = world_from_pelvis.transform.rotation
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quat = np.array([rxn.w, rxn.x, rxn.y, rxn.z])
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else:
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quat = low_state.imu_state.quaternion
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if self.config.imu_type == "torso":
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waist_yaw = low_state.motor_state[self.config.arm_waist_joint2motor_idx[0]].q
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waist_yaw_omega = low_state.motor_state[self.config.arm_waist_joint2motor_idx[0]].dq
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quat, ang_vel = transform_imu_data(
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waist_yaw=waist_yaw,
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waist_yaw_omega=waist_yaw_omega,
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imu_quat=quat,
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imu_omega=ang_vel)
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# NOTE(ycho): `ang_vel` is _probably_ in the pelvis frame,
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# since otherwise transform_imu_data() would be unnecessary for
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# `ang_vel`.
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base_ang_vel = ang_vel.squeeze(0)
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# TODO(ycho): check if the convention "q_base^{-1} @ g" holds.
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projected_gravity = get_gravity_orientation(quat)
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# Map `low_state` to index-mapped joint_{pos,vel}
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joint_pos = np.zeros(num_lab_joint,
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dtype=np.float32)
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joint_vel = np.zeros(num_lab_joint,
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dtype=np.float32)
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joint_pos[lab_from_mot] = [low_state.motor_state[i_mot].q for i_mot in
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range(len(lab_from_mot))]
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joint_pos -= config.lab_joint_offsets
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joint_vel[lab_from_mot] = [low_state.motor_state[i_mot].dq for i_mot in
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range(len(lab_from_mot))]
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actions = last_action
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obs = [
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base_ang_vel,
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projected_gravity,
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hands_command,
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joint_pos,
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joint_vel,
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actions,
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]
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# print([np.shape(o) for o in obs])
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return np.concatenate(obs, axis=-1)
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class Controller:
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def __init__(self, config: Config) -> None:
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self.config = config
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# init mapping tensor for joint order.
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self.mapping_tensor = torch.zeros((len(config.lab_joint), len(config.motor_joint)))
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for b_idx, b_joint in enumerate(config.motor_joint):
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if b_joint in config.lab_joint:
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a_idx = config.lab_joint.index(b_joint)
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self.mapping_tensor[a_idx, b_idx] = 1.0
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self.remote_controller = RemoteController()
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# Initialize the policy network
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self.policy = torch.jit.load(config.policy_path)
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self.action = np.zeros(config.num_actions, dtype=np.float32)
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# Data buffers
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self.obs = np.zeros(config.num_obs, dtype=np.float32)
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# command : x[m] y[m] z[m] heading[rad]
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self.cmd = np.array([0., 0., 0., 0.])
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self.counter = 0
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# ROS handles & helpers
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rp.init()
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self._node = rp.create_node("low_level_cmd_sender")
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self.tf_buffer = Buffer()
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self.tf_listener = TransformListener(self.tf_buffer, self._node)
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self.tf_broadcaster = TransformBroadcaster(self._node)
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self.obsmap = Observation(
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'../../resources/robots/g1_description/g1_29dof_with_hand_rev_1_0.urdf',
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config, self.tf_buffer)
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# FIXME(ycho): give `root_state_w`
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if True:
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q_mot = np.array(config.default_angles)
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q_pin = np.zeros_like(self.ikctrl.cfg.q)
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q_pin[self.pin_from_mot] = q_mot
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default_pose = self.ikctrl.fk(q_pin)
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xyz = default_pose.translation
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quat_wxyz = xyzw2wxyz(
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pin.Quaternion(
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default_pose.rotation).coeffs())
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self.default_pose_b = np.concatenate([xyz, quat_wxyz])
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# self.target_pose = np.copy(self.default_pose_b)
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self.target_pose = None
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# print('default_pose', self.default_pose_b)
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if config.msg_type == "hg":
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# g1 and h1_2 use the hg msg type
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self.low_cmd = LowCmdHG()
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self.low_state = LowStateHG()
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self.lowcmd_publisher_ = self._node.create_publisher(LowCmdHG,
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'lowcmd', 10)
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self.lowstate_subscriber = self._node.create_subscription(
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LowStateHG, 'lowstate', self.LowStateHgHandler, 10)
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self.mode_pr_ = MotorMode.PR
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self.mode_machine_ = 0
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elif config.msg_type == "go":
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raise ValueError(f"{config.msg_type} is not implemented yet.")
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else:
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raise ValueError("Invalid msg_type")
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# wait for the subscriber to receive data
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# self.wait_for_low_state()
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# Initialize the command msg
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if config.msg_type == "hg":
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init_cmd_hg(self.low_cmd, self.mode_machine_, self.mode_pr_)
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elif config.msg_type == "go":
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init_cmd_go(self.low_cmd, weak_motor=self.config.weak_motor)
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# NOTE(ycho):
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# if running from real robot:
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self.mode = Mode.wait
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# if running from rosbag:
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# self.mode = Mode.policy
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self._mode_change = True
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self._timer = self._node.create_timer(
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self.config.control_dt, self.run_wrapper)
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self._terminate = False
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try:
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rp.spin(self._node)
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except KeyboardInterrupt:
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print("KeyboardInterrupt")
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finally:
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self._node.destroy_timer(self._timer)
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create_damping_cmd(self.low_cmd)
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self.send_cmd(self.low_cmd)
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self._node.destroy_node()
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rp.shutdown()
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print("Exit")
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def LowStateHgHandler(self, msg: LowStateHG):
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self.low_state = msg
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self.mode_machine_ = self.low_state.mode_machine
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self.remote_controller.set(self.low_state.wireless_remote)
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def LowStateGoHandler(self, msg: LowStateGo):
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self.low_state = msg
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self.remote_controller.set(self.low_state.wireless_remote)
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def send_cmd(self, cmd: Union[LowCmdGo, LowCmdHG]):
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cmd.mode_machine = self.mode_machine_
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cmd.crc = CRC().Crc(cmd)
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size = len(cmd.motor_cmd)
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self.lowcmd_publisher_.publish(cmd)
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def wait_for_low_state(self):
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while self.low_state.crc == 0:
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print(self.low_state)
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time.sleep(self.config.control_dt)
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print("Successfully connected to the robot.")
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def zero_torque_state(self):
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if self.remote_controller.button[KeyMap.start] == 1:
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self._mode_change = True
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self.mode = Mode.default_pos
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else:
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create_zero_cmd(self.low_cmd)
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self.send_cmd(self.low_cmd)
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def prepare_default_pos(self):
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# move time 2s
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total_time = 2
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self.counter = 0
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self._num_step = int(total_time / self.config.control_dt)
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dof_idx = self.config.leg_joint2motor_idx + self.config.arm_waist_joint2motor_idx
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kps = self.config.kps + self.config.arm_waist_kps
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kds = self.config.kds + self.config.arm_waist_kds
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self._kps = [float(kp) for kp in kps]
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self._kds = [float(kd) for kd in kds]
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self._default_pos = np.concatenate(
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(self.config.default_angles, self.config.arm_waist_target), axis=0)
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self._dof_size = len(dof_idx)
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self._dof_idx = dof_idx
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# record the current pos
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# self._init_dof_pos = np.zeros(self._dof_size,
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# dtype=np.float32)
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# for i in range(self._dof_size):
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# self._init_dof_pos[i] = self.low_state.motor_state[dof_idx[i]].q
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self._init_dof_pos = np.zeros(29)
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for i in range(29):
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self._init_dof_pos[i] = self.low_state.motor_state[i].q
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def move_to_default_pos(self):
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# move to default pos
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if self.counter < self._num_step:
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alpha = self.counter / self._num_step
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# for j in range(self._dof_size):
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for j in range(29):
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# motor_idx = self._dof_idx[j]
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# target_pos = self._default_pos[j]
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motor_idx = j
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target_pos = self.config.default_angles[j]
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self.low_cmd.motor_cmd[motor_idx].q = (
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self._init_dof_pos[j] * (1 - alpha) + target_pos * alpha)
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self.low_cmd.motor_cmd[motor_idx].dq = 0.0
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self.low_cmd.motor_cmd[motor_idx].kp = self._kps[j]
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self.low_cmd.motor_cmd[motor_idx].kd = self._kds[j]
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self.low_cmd.motor_cmd[motor_idx].tau = 0.0
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self.send_cmd(self.low_cmd)
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self.counter += 1
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else:
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self._mode_change = True
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self.mode = Mode.damping
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def default_pos_state(self):
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if self.remote_controller.button[KeyMap.A] != 1:
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for i in range(len(self.config.leg_joint2motor_idx)):
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motor_idx = self.config.leg_joint2motor_idx[i]
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self.low_cmd.motor_cmd[motor_idx].q = float(
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self.config.default_angles[i])
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self.low_cmd.motor_cmd[motor_idx].dq = 0.0
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self.low_cmd.motor_cmd[motor_idx].kp = self._kps[i]
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self.low_cmd.motor_cmd[motor_idx].kd = self._kds[i]
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self.low_cmd.motor_cmd[motor_idx].tau = 0.0
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for i in range(len(self.config.arm_waist_joint2motor_idx)):
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motor_idx = self.config.arm_waist_joint2motor_idx[i]
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self.low_cmd.motor_cmd[motor_idx].q = float(
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self.config.arm_waist_target[i])
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self.low_cmd.motor_cmd[motor_idx].dq = 0.0
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self.low_cmd.motor_cmd[motor_idx].kp = self._kps[i]
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self.low_cmd.motor_cmd[motor_idx].kd = self._kds[i]
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self.low_cmd.motor_cmd[motor_idx].tau = 0.0
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self.send_cmd(self.low_cmd)
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else:
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self._mode_change = True
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self.mode = Mode.policy
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def run_policy(self):
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if self.remote_controller.button[KeyMap.select] == 1:
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self._mode_change = True
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self.mode = Mode.null
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return
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self.counter += 1
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# self.cmd[0] = x
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# self.cmd[1] = y
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# self.cmd[2] = z
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# self.cmd[3] = heading
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self.obs[:] = self.obsmap(self.low_state,
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self.action,
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self.cmd)
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# Get the action from the policy network
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obs_tensor = torch.from_numpy(self.obs).unsqueeze(0)
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obs_tensor = obs_tensor.detach().clone()
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self.action = self.policy(obs_tensor).detach().numpy().squeeze()
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self.action = self.action @ self.mapping_tensor.detach().cpu().numpy()
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target_dof_pos = self.config.default_angles + self.action * self.config.action_scale
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# Build low cmd
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for i in range(len(self.config.motor_joint)):
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self.low_cmd.motor_cmd[i].q = float(target_dof_pos[i])
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self.low_cmd.motor_cmd[i].dq = 0.0
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self.low_cmd.motor_cmd[i].kp = 1.0 * float(self.config.kps[i])
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self.low_cmd.motor_cmd[i].kd = 1.0 * float(self.config.kds[i])
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self.low_cmd.motor_cmd[i].tau = 0.0
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# reduce KP for non-arm joints
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# for i in self.mot_from_nonarm:
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# self.low_cmd.motor_cmd[i].kp = 0.05 * float(self.config.kps[i])
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# self.low_cmd.motor_cmd[i].kd = 0.05 * float(self.config.kds[i])
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# send the command
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self.send_cmd(self.low_cmd)
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def run_wrapper(self):
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# print("hello", self.mode,
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|
# self.mode == Mode.zero_torque)
|
|
if self.mode == Mode.wait:
|
|
if self.low_state.crc != 0:
|
|
self.mode = Mode.zero_torque
|
|
self.low_cmd.mode_machine = self.mode_machine_
|
|
print("Successfully connected to the robot.")
|
|
elif self.mode == Mode.zero_torque:
|
|
if self._mode_change:
|
|
print("Enter zero torque state.")
|
|
print("Waiting for the start signal...")
|
|
self._mode_change = False
|
|
self.zero_torque_state()
|
|
elif self.mode == Mode.default_pos:
|
|
if self._mode_change:
|
|
print("Moving to default pos.")
|
|
self._mode_change = False
|
|
self.prepare_default_pos()
|
|
self.move_to_default_pos()
|
|
elif self.mode == Mode.damping:
|
|
if self._mode_change:
|
|
print("Enter default pos state.")
|
|
print("Waiting for the Button A signal...")
|
|
self._mode_change = False
|
|
self.default_pos_state()
|
|
elif self.mode == Mode.policy:
|
|
if self._mode_change:
|
|
print("Run policy.")
|
|
self._mode_change = False
|
|
self.counter = 0
|
|
self.run_policy()
|
|
elif self.mode == Mode.null:
|
|
self._terminate = True
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import argparse
|
|
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument(
|
|
"config",
|
|
type=str,
|
|
help="config file name in the configs folder",
|
|
default="g1_nav.yaml")
|
|
args = parser.parse_args()
|
|
|
|
# Load config
|
|
config_path = f"{LEGGED_GYM_ROOT_DIR}/deploy/deploy_real/configs/{args.config}"
|
|
config = Config(config_path)
|
|
|
|
controller = Controller(config)
|