add task
This commit is contained in:
Yecheng Shao
parent
90956fc4df
commit
30dcc48623
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@ -2,9 +2,11 @@ from legged_gym import LEGGED_GYM_ROOT_DIR, LEGGED_GYM_ENVS_DIR
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from legged_gym.envs.go2.go2_config import GO2RoughCfg, GO2RoughCfgPPO
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from legged_gym.envs.h1.h1_config import H1RoughCfg, H1RoughCfgPPO
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from legged_gym.envs.h1_2.h1_2_config import H1_2RoughCfg, H1_2RoughCfgPPO
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from .base.legged_robot import LeggedRobot
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from legged_gym.utils.task_registry import task_registry
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task_registry.register("go2", LeggedRobot, GO2RoughCfg(), GO2RoughCfgPPO())
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task_registry.register("h1", LeggedRobot, H1RoughCfg(), H1RoughCfgPPO())
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task_registry.register("h1_2", LeggedRobot, H1_2RoughCfg(), H1_2RoughCfgPPO())
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@ -0,0 +1,121 @@
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from legged_gym.envs.base.legged_robot_config import LeggedRobotCfg, LeggedRobotCfgPPO
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class H1_2RoughCfg(LeggedRobotCfg):
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class init_state(LeggedRobotCfg.init_state):
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pos = [0.0, 0.0, 1.0] # x,y,z [m]
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default_joint_angles = { # = target angles [rad] when action = 0.0
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'left_hip_yaw_joint': 0,
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'left_hip_roll_joint': 0,
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'left_hip_pitch_joint': -0.6,
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'left_knee_joint': 1.2,
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'left_ankle_pitch_joint': -0.6,
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'left_ankle_roll_joint': 0.0,
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'right_hip_yaw_joint': 0,
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'right_hip_roll_joint': 0,
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'right_hip_pitch_joint': -0.6,
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'right_knee_joint': 1.2,
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'right_ankle_pitch_joint': -0.6,
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'right_ankle_roll_joint': 0.0,
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'torso_joint': 0,
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'left_shoulder_pitch_joint': 0.4,
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'left_shoulder_roll_joint': 0,
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'left_shoulder_yaw_joint': 0,
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'left_elbow_pitch_joint': 0.3,
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'right_shoulder_pitch_joint': 0.4,
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'right_shoulder_roll_joint': 0,
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'right_shoulder_yaw_joint': 0,
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'right_elbow_pitch_joint': 0.3,
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}
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class env(LeggedRobotCfg.env):
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num_actions = 21
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num_observations = 12 + num_actions * 3
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num_envs = 8192
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class control(LeggedRobotCfg.control):
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# PD Drive parameters:
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control_type = 'P'
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# PD Drive parameters:
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stiffness = {
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'hip_yaw_joint': 200.,
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'hip_roll_joint': 200.,
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'hip_pitch_joint': 200.,
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'knee_joint': 300.,
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'ankle_pitch_joint': 60.,
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'ankle_roll_joint': 40.,
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'torso_joint': 600.,
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'shoulder_pitch_joint': 80.,
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'shoulder_roll_joint': 80.,
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'shoulder_yaw_joint': 40.,
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'elbow_pitch_joint': 60.,
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} # [N*m/rad]
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damping = {
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'hip_yaw_joint': 5.0,
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'hip_roll_joint': 5.0,
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'hip_pitch_joint': 5.0,
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'knee_joint': 7.5,
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'ankle_pitch_joint': 1.0,
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'ankle_roll_joint': 0.3,
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'torso_joint': 15.0,
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'shoulder_pitch_joint': 2.0,
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'shoulder_roll_joint': 2.0,
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'shoulder_yaw_joint': 1.0,
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'elbow_pitch_joint': 1.0,
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} # [N*m/rad] # [N*m*s/rad]
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# action scale: target angle = actionScale * action + defaultAngle
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action_scale = 0.25
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# decimation: Number of control action updates @ sim DT per policy DT
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decimation = 10
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class asset(LeggedRobotCfg.asset):
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file = '{LEGGED_GYM_ROOT_DIR}/resources/robots/h1_2/h1_2_simplified.urdf'
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name = "h1_2"
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foot_name = "ankle_roll"
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penalize_contacts_on = []
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terminate_after_contacts_on = []
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self_collisions = 1 # 1 to disable, 0 to enable...bitwise filter
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flip_visual_attachments = False
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armature = 6e-4 # stablize semi-euler integration for end effectors
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class sim(LeggedRobotCfg.sim):
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dt = 0.002 # stablize semi-euler integration for end effectors
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class rewards(LeggedRobotCfg.rewards):
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soft_dof_pos_limit = 0.9
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base_height_target = 0.98
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class scales(LeggedRobotCfg.rewards.scales):
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tracking_lin_vel = 1.0
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tracking_ang_vel = 0.5
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lin_vel_z = -0.2
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ang_vel_xy = -0.1
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orientation = -0.1
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base_height = -10.0
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dof_acc = -3.5e-9
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feet_air_time = 1.0
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collision = 0.0
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action_rate = -0.001
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torques = 0.0
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dof_pos_limits = -1.0
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only_positive_rewards = False # if true negative total rewards are clipped at zero (avoids early termination problems)
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class normalization(LeggedRobotCfg.normalization):
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clip_actions = 10.0
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class H1_2RoughCfgPPO(LeggedRobotCfgPPO):
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class policy(LeggedRobotCfgPPO.policy):
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init_noise_std = 0.3
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activation = 'tanh'
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class runner(LeggedRobotCfgPPO.runner):
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run_name = ''
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experiment_name = 'h1_2'
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@ -1,5 +1,4 @@
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import sys
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sys.path.append("/home/unitree/unitree_rl_gym")
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from legged_gym import LEGGED_GYM_ROOT_DIR
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import os
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@ -2,7 +2,6 @@ import numpy as np
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import os
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from datetime import datetime
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import sys
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sys.path.append("/home/unitree/unitree_rl_gym/")
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import isaacgym
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from legged_gym.envs import *
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@ -4,7 +4,6 @@ from typing import Tuple
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import torch
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import numpy as np
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import sys
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sys.path.append("/home/unitree/unitree_rl_gym/rsl_rl")
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from rsl_rl.env import VecEnv
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from rsl_rl.runners import OnPolicyRunner
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@ -0,0 +1,11 @@
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from setuptools import find_packages
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from distutils.core import setup
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setup(name='unitree_rl_gym',
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version='1.0.0',
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author='Unitree Robotics',
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license="BSD-3-Clause",
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packages=find_packages(),
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author_email='support@unitree.com',
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description='Template RL environments for Unitree Robots',
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install_requires=['isaacgym', 'rsl-rl', 'matplotlib', 'numpy==1.20', 'tensorboard'])
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