726 lines
26 KiB
Python
726 lines
26 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 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 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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from math_utils import *
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import random as rd
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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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def axis_angle_from_quat(quat: np.ndarray, eps: float = 1.0e-6) -> np.ndarray:
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"""Convert rotations given as quaternions to axis/angle.
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Args:
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quat: The quaternion orientation in (w, x, y, z). Shape is (..., 4).
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eps: The tolerance for Taylor approximation. Defaults to 1.0e-6.
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Returns:
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Rotations given as a vector in axis angle form. Shape is (..., 3).
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The vector's magnitude is the angle turned anti-clockwise in radians around the vector's direction.
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Reference:
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https://github.com/facebookresearch/pytorch3d/blob/main/pytorch3d/transforms/rotation_conversions.py#L526-L554
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"""
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# Modified to take in quat as [q_w, q_x, q_y, q_z]
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# Quaternion is [q_w, q_x, q_y, q_z] = [cos(theta/2), n_x * sin(theta/2), n_y * sin(theta/2), n_z * sin(theta/2)]
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# Axis-angle is [a_x, a_y, a_z] = [theta * n_x, theta * n_y, theta * n_z]
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# Thus, axis-angle is [q_x, q_y, q_z] / (sin(theta/2) / theta)
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# When theta = 0, (sin(theta/2) / theta) is undefined
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# However, as theta --> 0, we can use the Taylor approximation 1/2 -
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# theta^2 / 48
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quat = quat * (1.0 - 2.0 * (quat[..., 0:1] < 0.0))
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mag = np.linalg.norm(quat[..., 1:], axis=-1)
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half_angle = np.arctan2(mag, quat[..., 0])
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angle = 2.0 * half_angle
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# check whether to apply Taylor approximation
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sin_half_angles_over_angles = np.where(
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np.abs(angle) > eps,
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np.sin(half_angle) / angle,
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0.5 - angle * angle / 48
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)
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return quat[..., 1:4] / sin_half_angles_over_angles[..., None]
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def quat_rotate(q: np.ndarray, v: np.ndarray) -> np.ndarray:
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"""Rotate a vector by a quaternion along the last dimension of q and v.
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Args:
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q: The quaternion in (w, x, y, z). Shape is (..., 4).
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v: The vector in (x, y, z). Shape is (..., 3).
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Returns:
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The rotated vector in (x, y, z). Shape is (..., 3).
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"""
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q_w = q[..., 0]
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q_vec = q[..., 1:]
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a = v * (2.0 * q_w**2 - 1.0)[..., None]
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b = np.cross(q_vec, v, axis=-1) * q_w[..., None] * 2.0
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c = q_vec * np.einsum("...i,...i->...", q_vec, v)[..., None] * 2.0
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return a + b + c
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def quat_rotate_inverse(q: np.ndarray, v: np.ndarray) -> np.ndarray:
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"""Rotate a vector by the inverse of a quaternion along the last dimension of q and v.
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Args:
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q: The quaternion in (w, x, y, z). Shape is (..., 4).
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v: The vector in (x, y, z). Shape is (..., 3).
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Returns:
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The rotated vector in (x, y, z). Shape is (..., 3).
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"""
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q_w = q[..., 0]
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q_vec = q[..., 1:]
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a = v * (2.0 * q_w**2 - 1.0)[..., None]
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b = np.cross(q_vec, v, axis=-1) * q_w[..., None] * 2.0
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c = q_vec * np.einsum("...i,...i->...", q_vec, v)[..., None] * 2.0
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return a - b + c
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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 = (axa + np.pi) % (2 * np.pi)
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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('../../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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i.e. k_to[index_map] = k_from
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Missing values are set to -1.
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"""
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out = []
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for k in k_to:
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try:
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i = k_from.index(k)
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except ValueError:
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i = -1
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out.append(i)
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return out
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def interpolate_position(pos1, pos2, n_segments):
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increments = (pos2 - pos1) / n_segments
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interp_pos = [pos1 + increments * p for p in range(n_segments)]
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interp_pos.append(pos2)
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return interp_pos
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class eetrack:
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def __init__(self, root_state_w):
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self.eetrack_midpt = root_state_w.clone()
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self.eetrack_midpt[1] += 0.3
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self.eetrack_end = None
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self.eetrack_subgoal = None
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self.number_of_subgoals = 30
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self.eetrack_line_length = 0.3
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self.device = "cuda"
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self.create_eetrack()
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self.eetrack_subgoal = self.create_subgoal()
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self.sg_idx = 0
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self.init_time = rp.time.Time() + 1.0 # first subgoal sampling time = 1.0s
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def create_eetrack(self):
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self.eetrack_start = self.eetrack_midpt.clone()
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self.eetrack_end = self.eetrack_midpt.clone()
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is_hor = rd.choice([True, False])
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eetrack_offset = rd.uniform(-0.5, 0.5)
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# For testing
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is_hor = True
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eetrack_offset = 0.0
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if is_hor:
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self.eetrack_start[2] += eetrack_offset
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self.eetrack_end[2] += eetrack_offset
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self.eetrack_start[0] -= (self.eetrack_line_length) / 2.
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self.eetrack_end[0] += (self.eetrack_line_length) / 2.
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else:
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self.eetrack_start[0] += eetrack_offset
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self.eetrack_end[0] += eetrack_offset
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self.eetrack_start[2] += (self.eetrack_line_length) / 2.
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self.eetrack_end[2] -= (self.eetrack_line_length) / 2.
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return self.eetrack_start, self.eetrack_end
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def create_direction(self):
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angle_from_eetrack_line = torch.rand(1, device=self.device) * np.pi
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angle_from_xyplane_in_global_frame = torch.rand(1, device=self.device) * np.pi - np.pi/2
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# For testing
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angle_from_eetrack_line = torch.rand(1, device=self.device) * np.pi/2
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angle_from_xyplane_in_global_frame = torch.rand(1, device=self.device) * 0
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roll = torch.zeros(1, device=self.device)
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pitch = angle_from_xyplane_in_global_frame
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yaw = angle_from_eetrack_line
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euler = torch.stack([roll, pitch, yaw], dim=1)
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quat = math_utils.quat_from_euler_xyz(euler[:,0], euler[:,1], euler[:,2])
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return quat
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def create_subgoal(self):
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eetrack_subgoals = interpolate_position(self.eetrack_start, self.eetrack_end, self.number_of_subgoals)
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eetrack_subgoals = [
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(
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l.clone().to(self.device, dtype=torch.float32)
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if isinstance(l, torch.Tensor)
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else torch.tensor(l, device=self.device, dtype=torch.float32)
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)
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for l in eetrack_subgoals
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]
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eetrack_subgoals = torch.stack(eetrack_subgoals,axis=1)
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eetrack_ori = self.create_direction().unsqueeze(1).repeat(1, self.number_of_subgoals + 1, 1)
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# welidng_subgoals -> Nenv x Npoints x (3 + 4)
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return torch.cat([eetrack_subgoals, eetrack_ori], dim=2)
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def update_command(self):
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time = self.init_time - rp.time.Time()
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if (time>=0):
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self.sg_idx = time / 0.1 + 1
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self.sg_idx.clamp_(0, self.number_of_subgoals + 1)
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self.next_command_s_left = self.eetrack_subgoal[self.sg_idx]
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def get_command(self, root_state_w):
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self.update_command()
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pos_hand_b_left, quat_hand_b_left = body_pose_axa("left_hand_palm_link")
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lerp_command_w_left = self.next_command_s_left
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# lerp_command_b_left = math_utils.subtract_frame_transforms(
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# root_state_w[..., 0:3],
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# root_state_w[..., 3:7],
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# lerp_command_w_left[:, 0:3],
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# lerp_command_w_left[:, 3:7],
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# )
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lerp_command_b_left = lerp_command_w_left
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pos_delta_b_left, rot_delta_b_left = math_utils.compute_pose_error(
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pos_hand_b_left,
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quat_hand_b_left,
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lerp_command_b_left[:, :3],
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lerp_command_b_left[:, 3:],
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)
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axa_delta_b_left = math_utils.wrap_to_pi(rot_delta_b_left)
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hand_command = torch.cat((pos_delta_b_left, axa_delta_b_left), dim=-1)
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return hand_command
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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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# observation terms (order preserved)
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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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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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base_ang_vel = ang_vel
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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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fp_l = body_pose(self.tf_buffer, 'left_ankle_roll_link')
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fp_r = body_pose(self.tf_buffer, 'right_ankle_roll_link')
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foot_pose = np.concatenate([fp_l[0], fp_r[0], fp_l[1], fp_r[1]])
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hp_l = body_pose(self.tf_buffer, 'left_hand_palm_link')
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hp_r = body_pose(self.tf_buffer, 'right_hand_palm_link')
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hand_pose = np.concatenate([hp_l[0], hp_r[0], hp_l[1], hp_r[1]])
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# FIXME(ycho): implement com_pos_wrt_pelvis
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projected_com = compute_com(self.tf_buffer, self.links)
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# projected_zmp = _ # IMPOSSIBLE
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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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# Given as delta_pos {xyz,axa}; i.e. 6D vector
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# hands_command = self.eetrack.get_command()
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right_arm_com = compute_com(self.tf_buffer, [
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"right_shoulder_pitch_link",
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"right_shoulder_roll_link",
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"right_shoulder_yaw_link",
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"right_elbow_link",
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"right_wrist_pitch_link"
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"right_wrist_roll_link",
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"right_wrist_yaw_link"
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])
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left_arm_com = compute_com(self.tf_buffer, [
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"left_shoulder_pitch_link",
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"left_shoulder_roll_link",
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"left_shoulder_yaw_link",
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"left_elbow_link",
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"left_wrist_pitch_link"
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"left_wrist_roll_link",
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"left_wrist_yaw_link"
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])
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if True: # hack
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lf_from_pelvis = self.tf_buffer.lookup_transform(
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'left_ankle_roll_link', # to
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'pelvis',
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rp.time.Time()
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)
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rf_from_pelvis = self.tf_buffer.lookup_transform(
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'right_ankle_roll_link', # to
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'pelvis',
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rp.time.Time()
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)
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# NOTE(ycho): we assume at least one of the feet is on the ground
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# and use the higher of the two as the pelvis height.
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pelvis_height = max(lf_from_pelvis.transform.translation.z,
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rf_from_pelvis.transform.translation.z)
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pelvis_height = [pelvis_height]
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else:
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pelvis_height = np.abs(np.dot(
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projected_gravity, # world frame
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fp_l[0]
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)
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)
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obs = [
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base_ang_vel,
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projected_gravity,
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foot_pose,
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hand_pose,
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projected_com,
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joint_pos,
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joint_vel,
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actions,
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hands_command,
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right_arm_com,
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left_arm_com,
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pelvis_height
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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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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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self.ikctrl = IKCtrl(
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'../../resources/robots/g1_description/g1_29dof_with_hand_rev_1_0.urdf',
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config.arm_joint)
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self.lim_lo_pin = self.ikctrl.robot.model.lowerPositionLimit
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self.lim_hi_pin = self.ikctrl.robot.model.upperPositionLimit
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# == build index map ==
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arm_joint = config.arm_joint
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self.mot_from_pin = index_map(
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self.config.motor_joint,
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self.ikctrl.joint_names)
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self.pin_from_mot = index_map(
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self.ikctrl.joint_names,
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self.config.motor_joint
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)
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self.mot_from_arm = index_map(
|
|
self.config.motor_joint,
|
|
self.config.arm_joint
|
|
)
|
|
self.mot_from_nonarm = index_map(
|
|
self.config.motor_joint,
|
|
self.config.non_arm_joint
|
|
)
|
|
|
|
# Data buffers
|
|
self.obs = np.zeros(config.num_obs, dtype=np.float32)
|
|
self.cmd = np.array([0.0, 0, 0])
|
|
self.counter = 0
|
|
|
|
# ROS handles & helpers
|
|
rp.init()
|
|
self._node = rp.create_node("low_level_cmd_sender")
|
|
self.tf_buffer = Buffer()
|
|
self.tf_listener = TransformListener(self.tf_buffer, self._node)
|
|
self.obsmap = Observation(
|
|
'../../resources/robots/g1_description/g1_29dof_with_hand_rev_1_0.urdf',
|
|
config, self.tf_buffer)
|
|
# FIXME(ycho): give `root_state_w`
|
|
# self.eetrack = eetrack(root_state_w=None)
|
|
|
|
if config.msg_type == "hg":
|
|
# g1 and h1_2 use the hg msg type
|
|
|
|
self.low_cmd = LowCmdHG()
|
|
self.low_state = LowStateHG()
|
|
|
|
self.lowcmd_publisher_ = self._node.create_publisher(LowCmdHG,
|
|
'lowcmd', 10)
|
|
self.lowstate_subscriber = self._node.create_subscription(
|
|
LowStateHG, 'lowstate', self.LowStateHgHandler, 10)
|
|
self.mode_pr_ = MotorMode.PR
|
|
self.mode_machine_ = 0
|
|
|
|
elif config.msg_type == "go":
|
|
raise ValueError(f"{config.msg_type} is not implemented yet.")
|
|
|
|
else:
|
|
raise ValueError("Invalid msg_type")
|
|
|
|
# wait for the subscriber to receive data
|
|
# self.wait_for_low_state()
|
|
|
|
# Initialize the command msg
|
|
if config.msg_type == "hg":
|
|
init_cmd_hg(self.low_cmd, self.mode_machine_, self.mode_pr_)
|
|
elif config.msg_type == "go":
|
|
init_cmd_go(self.low_cmd, weak_motor=self.config.weak_motor)
|
|
|
|
self.mode = Mode.wait
|
|
self._mode_change = True
|
|
self._timer = self._node.create_timer(
|
|
self.config.control_dt, self.run_wrapper)
|
|
self._terminate = False
|
|
try:
|
|
rp.spin(self._node)
|
|
except KeyboardInterrupt:
|
|
print("KeyboardInterrupt")
|
|
finally:
|
|
self._node.destroy_timer(self._timer)
|
|
create_damping_cmd(self.low_cmd)
|
|
self.send_cmd(self.low_cmd)
|
|
self._node.destroy_node()
|
|
rp.shutdown()
|
|
print("Exit")
|
|
|
|
def LowStateHgHandler(self, msg: LowStateHG):
|
|
self.low_state = msg
|
|
self.mode_machine_ = self.low_state.mode_machine
|
|
self.remote_controller.set(self.low_state.wireless_remote)
|
|
|
|
def LowStateGoHandler(self, msg: LowStateGo):
|
|
self.low_state = msg
|
|
self.remote_controller.set(self.low_state.wireless_remote)
|
|
|
|
def send_cmd(self, cmd: Union[LowCmdGo, LowCmdHG]):
|
|
cmd.mode_machine = self.mode_machine_
|
|
cmd.crc = CRC().Crc(cmd)
|
|
size = len(cmd.motor_cmd)
|
|
self.lowcmd_publisher_.publish(cmd)
|
|
|
|
def wait_for_low_state(self):
|
|
while self.low_state.crc == 0:
|
|
print(self.low_state)
|
|
time.sleep(self.config.control_dt)
|
|
print("Successfully connected to the robot.")
|
|
|
|
def zero_torque_state(self):
|
|
if self.remote_controller.button[KeyMap.start] == 1:
|
|
self._mode_change = True
|
|
self.mode = Mode.default_pos
|
|
else:
|
|
create_zero_cmd(self.low_cmd)
|
|
self.send_cmd(self.low_cmd)
|
|
|
|
def prepare_default_pos(self):
|
|
# move time 2s
|
|
total_time = 2
|
|
self.counter = 0
|
|
self._num_step = int(total_time / self.config.control_dt)
|
|
|
|
dof_idx = self.config.leg_joint2motor_idx + self.config.arm_waist_joint2motor_idx
|
|
kps = self.config.kps + self.config.arm_waist_kps
|
|
kds = self.config.kds + self.config.arm_waist_kds
|
|
self._kps = [float(kp) for kp in kps]
|
|
self._kds = [float(kd) for kd in kds]
|
|
self._default_pos = np.concatenate(
|
|
(self.config.default_angles, self.config.arm_waist_target), axis=0)
|
|
self._dof_size = len(dof_idx)
|
|
self._dof_idx = dof_idx
|
|
|
|
# record the current pos
|
|
self._init_dof_pos = np.zeros(self._dof_size,
|
|
dtype=np.float32)
|
|
for i in range(self._dof_size):
|
|
self._init_dof_pos[i] = self.low_state.motor_state[dof_idx[i]].q
|
|
|
|
def move_to_default_pos(self):
|
|
# move to default pos
|
|
if self.counter < self._num_step:
|
|
alpha = self.counter / self._num_step
|
|
for j in range(self._dof_size):
|
|
motor_idx = self._dof_idx[j]
|
|
target_pos = self._default_pos[j]
|
|
self.low_cmd.motor_cmd[motor_idx].q = (
|
|
self._init_dof_pos[j] * (1 - alpha) + target_pos * alpha)
|
|
self.low_cmd.motor_cmd[motor_idx].dq = 0.0
|
|
self.low_cmd.motor_cmd[motor_idx].kp = self._kps[j]
|
|
self.low_cmd.motor_cmd[motor_idx].kd = self._kds[j]
|
|
self.low_cmd.motor_cmd[motor_idx].tau = 0.0
|
|
self.send_cmd(self.low_cmd)
|
|
self.counter += 1
|
|
else:
|
|
self._mode_change = True
|
|
self.mode = Mode.damping
|
|
|
|
def default_pos_state(self):
|
|
if self.remote_controller.button[KeyMap.A] != 1:
|
|
for i in range(len(self.config.leg_joint2motor_idx)):
|
|
motor_idx = self.config.leg_joint2motor_idx[i]
|
|
self.low_cmd.motor_cmd[motor_idx].q = float(
|
|
self.config.default_angles[i])
|
|
self.low_cmd.motor_cmd[motor_idx].dq = 0.0
|
|
self.low_cmd.motor_cmd[motor_idx].kp = self._kps[i]
|
|
self.low_cmd.motor_cmd[motor_idx].kd = self._kds[i]
|
|
self.low_cmd.motor_cmd[motor_idx].tau = 0.0
|
|
for i in range(len(self.config.arm_waist_joint2motor_idx)):
|
|
motor_idx = self.config.arm_waist_joint2motor_idx[i]
|
|
self.low_cmd.motor_cmd[motor_idx].q = float(
|
|
self.config.arm_waist_target[i])
|
|
self.low_cmd.motor_cmd[motor_idx].dq = 0.0
|
|
self.low_cmd.motor_cmd[motor_idx].kp = self._kps[i]
|
|
self.low_cmd.motor_cmd[motor_idx].kd = self._kds[i]
|
|
self.low_cmd.motor_cmd[motor_idx].tau = 0.0
|
|
self.send_cmd(self.low_cmd)
|
|
else:
|
|
self._mode_change = True
|
|
self.mode = Mode.policy
|
|
|
|
def run_policy(self):
|
|
if self.remote_controller.button[KeyMap.select] == 1:
|
|
self._mode_change = True
|
|
self.mode = Mode.null
|
|
return
|
|
self.counter += 1
|
|
|
|
# TODO(ycho): consider using `cmd` for `hands_command`
|
|
# self.cmd[0] = self.remote_controller.ly
|
|
# self.cmd[1] = self.remote_controller.lx * -1
|
|
# self.cmd[2] = self.remote_controller.rx * -1
|
|
|
|
# FIXME(ycho): implement `_hands_command_`
|
|
# to use the output of `eetrack`.
|
|
_hands_command_ = np.zeros(6)
|
|
|
|
self.obs[:] = self.obsmap(self.low_state,
|
|
self.action,
|
|
_hands_command_)
|
|
|
|
# Get the action from the policy network
|
|
obs_tensor = torch.from_numpy(self.obs).unsqueeze(0)
|
|
self.action = self.policy(obs_tensor).detach().numpy().squeeze()
|
|
|
|
non_arm_joint_pos = self.action[..., :22]
|
|
left_arm_residual = self.action[..., 22:29]
|
|
|
|
q_pin = np.zeros_like(self.ikctrl.cfg.q0)
|
|
for i_mot in range(len(self.config.motor_joint)):
|
|
i_pin = self.pin_from_mot[i_mot]
|
|
q_pin[i_pin] = self.low_state.motor_state[i_mot].q
|
|
res_q_ik = self.ikctrl(
|
|
q_pin,
|
|
_hands_command_
|
|
)
|
|
|
|
target_dof_pos = np.zeros(29)
|
|
for i_act in range(len(res_q_ik)):
|
|
i_mot = self.mot_from_act[i_act]
|
|
i_pin = self.pin_from_mot[i_mot]
|
|
target_q = (
|
|
self.low_state.motor_state[i_mot].q
|
|
+ res_q_ik[i_act]
|
|
+ np.clip(0.3 * left_arm_residual[i_act],
|
|
-0.2, 0.2)
|
|
)
|
|
target_q = np.clip(target_q,
|
|
self.lim_lo_pin[i_pin],
|
|
self.lim_hi_pin[i_pin])
|
|
target_dof_pos[i_mot] = target_q
|
|
|
|
# Build low cmd
|
|
for i in range(len(self.config.motor_joint)):
|
|
self.low_cmd.motor_cmd[i].q = float(target_dof_pos[i])
|
|
self.low_cmd.motor_cmd[i].dq = 0.0
|
|
self.low_cmd.motor_cmd[i].kp = 0.0 * float(self.config.kps[i])
|
|
self.low_cmd.motor_cmd[i].kd = 0.0 * float(self.config.kds[i])
|
|
self.low_cmd.motor_cmd[i].tau = 0.0
|
|
|
|
# send the command
|
|
self.send_cmd(self.low_cmd)
|
|
|
|
def run_wrapper(self):
|
|
# print("hello", self.mode,
|
|
# 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
|
|
|
|
# time.sleep(self.config.control_dt)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import argparse
|
|
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument(
|
|
"config",
|
|
type=str,
|
|
help="config file name in the configs folder",
|
|
default="g1.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)
|