can go is Lv0
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# Copyright (c) 2022-2025, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
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# All rights reserved.
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#
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# SPDX-License-Identifier: BSD-3-Clause
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import math
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from pathlib import Path
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import isaaclab.sim as sim_utils
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from isaaclab.actuators import ImplicitActuatorCfg
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from isaaclab.assets import ArticulationCfg, AssetBaseCfg
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from isaaclab.envs import ManagerBasedRLEnvCfg
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from isaaclab.managers import EventTermCfg as EventTerm
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from isaaclab.managers import ObservationGroupCfg as ObsGroup
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from isaaclab.managers import ObservationTermCfg as ObsTerm
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from isaaclab.managers import RewardTermCfg as RewTerm
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from isaaclab.managers import SceneEntityCfg
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from isaaclab.managers import TerminationTermCfg as DoneTerm
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from isaaclab.scene import InteractiveSceneCfg
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from isaaclab.sensors import ContactSensorCfg
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from isaaclab.utils.configclass import configclass
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from isaaclab.utils.noise import UniformNoiseCfg
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import isaaclab_tasks.manager_based.locomotion.velocity.mdp as velocity_mdp
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from . import mdp
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##
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# Pre-defined configs
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##
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DEMO_ROOT = Path(__file__).resolve().parents[6]
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URDF_PATH = DEMO_ROOT / "bot" / "2foot" / "urdf" / "2foot.urdf"
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BOT_PACKAGE_PATH = DEMO_ROOT / "bot" / "2foot"
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JOINT_NAMES = [
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"jlf0_link",
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"jlf1_link",
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"jlf2_link",
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"jlf3_link",
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"jrf0_link",
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"jrf1_link",
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"jrf2_link",
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"jrf3_link",
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]
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TWOFOOTBOT_CFG = ArticulationCfg(
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spawn=sim_utils.UrdfFileCfg(
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asset_path=str(URDF_PATH),
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fix_base=False,
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activate_contact_sensors=True,
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ros_package_paths=[{"name": "2foot", "path": str(BOT_PACKAGE_PATH)}],
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joint_drive=sim_utils.UrdfFileCfg.JointDriveCfg(
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drive_type="force",
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target_type="position",
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gains=sim_utils.UrdfFileCfg.JointDriveCfg.PDGainsCfg(stiffness=17.0, damping=0.3),
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),
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rigid_props=sim_utils.RigidBodyPropertiesCfg(
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disable_gravity=False,
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max_linear_velocity=100.0,
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max_angular_velocity=100.0,
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max_depenetration_velocity=5.0,
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),
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articulation_props=sim_utils.ArticulationRootPropertiesCfg(
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enabled_self_collisions=False,
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solver_position_iteration_count=8,
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solver_velocity_iteration_count=1,
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),
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),
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init_state=ArticulationCfg.InitialStateCfg(
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pos=(0.0, 0.0, 0.22),
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joint_pos={joint_name: 0.0 for joint_name in JOINT_NAMES},
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joint_vel={".*": 0.0},
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),
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actuators={
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"legs": ImplicitActuatorCfg(
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joint_names_expr=JOINT_NAMES,
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effort_limit_sim=0.5,
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velocity_limit_sim=5.0,
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stiffness=5.0,
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damping=0.3,
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)
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},
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)
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##
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# Scene definition
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##
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@configclass
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class TwofootbotdemoSceneCfg(InteractiveSceneCfg):
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"""Flat-ground scene for the 2foot velocity-tracking task."""
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# ground plane
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ground = AssetBaseCfg(
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prim_path="/World/ground",
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spawn=sim_utils.GroundPlaneCfg(size=(100.0, 100.0)),
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)
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# robot
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robot: ArticulationCfg = TWOFOOTBOT_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
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contact_forces = None
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# lights
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dome_light = AssetBaseCfg(
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prim_path="/World/DomeLight",
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spawn=sim_utils.DomeLightCfg(color=(0.9, 0.9, 0.9), intensity=500.0),
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)
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##
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# MDP settings
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##
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@configclass
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class ActionsCfg:
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"""Action specifications for the MDP."""
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joint_pos = velocity_mdp.JointPositionActionCfg(
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asset_name="robot", joint_names=JOINT_NAMES, scale=0.5, use_default_offset=True
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)
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@configclass
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class CommandsCfg:
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"""The arrow points along +X at a fixed walking speed."""
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base_velocity = velocity_mdp.UniformVelocityCommandCfg(
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asset_name="robot",
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resampling_time_range=(10.0, 10.0),
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rel_standing_envs=0.0,
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rel_heading_envs=0.0,
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heading_command=False,
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debug_vis=True,
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ranges=velocity_mdp.UniformVelocityCommandCfg.Ranges(
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lin_vel_x=(0.35, 0.35),
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lin_vel_y=(0.0, 0.0),
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ang_vel_z=(0.0, 0.0),
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heading=(-math.pi, math.pi),
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),
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)
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@configclass
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class ObservationsCfg:
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"""Observation specifications for the MDP."""
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@configclass
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class PolicyCfg(ObsGroup):
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"""Observations for policy group."""
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# observation terms (order preserved)
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base_lin_vel = ObsTerm(func=velocity_mdp.base_lin_vel, noise=UniformNoiseCfg(n_min=-0.1, n_max=0.1))
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base_ang_vel = ObsTerm(func=velocity_mdp.base_ang_vel, noise=UniformNoiseCfg(n_min=-0.2, n_max=0.2))
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projected_gravity = ObsTerm(func=velocity_mdp.projected_gravity)
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velocity_commands = ObsTerm(
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func=velocity_mdp.generated_commands, params={"command_name": "base_velocity"}
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)
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joint_pos_rel = ObsTerm(func=velocity_mdp.joint_pos_rel, params={"asset_cfg": SceneEntityCfg("robot")})
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joint_vel_rel = ObsTerm(func=velocity_mdp.joint_vel_rel, params={"asset_cfg": SceneEntityCfg("robot")})
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actions = ObsTerm(func=velocity_mdp.last_action)
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def __post_init__(self) -> None:
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self.enable_corruption = False
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self.concatenate_terms = True
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# observation groups
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policy: PolicyCfg = PolicyCfg()
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@configclass
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class EventCfg:
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"""Configuration for events."""
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# reset
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reset_base = EventTerm(
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func=velocity_mdp.reset_root_state_uniform,
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mode="reset",
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params={
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"pose_range": {"x": (-0.2, 0.2), "y": (-0.05, 0.05), "yaw": (-0.1, 0.1)},
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"velocity_range": {"x": (-0.05, 0.05), "y": (-0.05, 0.05), "z": (-0.05, 0.05)},
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},
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)
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reset_joints = EventTerm(
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func=velocity_mdp.reset_joints_by_scale,
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mode="reset",
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params={
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"position_range": (0.9, 1.1),
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"velocity_range": (0.0, 0.0),
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},
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)
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@configclass
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class RewardsCfg:
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"""Reward terms for the MDP."""
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# (1) Constant running reward
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# 轨迹线性速度奖励项
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track_lin_vel = RewTerm( # 定义一个奖励项，用于跟踪线性速度
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func=velocity_mdp.track_lin_vel_xy_exp, # 使用velocity_mdp模块中的track_lin_vel_xy_exp函数作为奖励计算方法
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weight=5.0,
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params={"command_name": "base_velocity", "std": math.sqrt(0.25)},
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)
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# 创建奖励项，用于控制机器人的各种行为
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upright = RewTerm(func=velocity_mdp.flat_orientation_l2, weight=-1.0) # 控制机器人保持直立姿态，权重为-1.0
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vertical_velocity = RewTerm(func=velocity_mdp.lin_vel_z_l2, weight=-1.0) # 控制机器人垂直方向速度，权重为-1.0
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angular_velocity = RewTerm(func=velocity_mdp.ang_vel_xy_l2, weight=-0.05) # 控制机器人角速度，权重为-0.05
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action_rate = RewTerm(func=velocity_mdp.action_rate_l2, weight=-0.01) # 控制机器人动作变化率，权重为-0.01
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joint_acceleration = RewTerm(func=velocity_mdp.joint_acc_l2, weight=-2.5e-7) # 控制机器人关节加速度，权重为-2.5e-7
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joint_limits = RewTerm(func=velocity_mdp.joint_pos_limits, weight=-1.0) # 确保机器人关节位置在限制范围内，权重为-1.0
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@configclass
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class TerminationsCfg:
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"""Termination terms for the MDP."""
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# (1) Time out
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time_out = DoneTerm(func=mdp.time_out, time_out=True)
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# (2) The robot has tipped too far from upright.
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fallen_orientation = DoneTerm(
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func=mdp.bad_orientation,
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params={"limit_angle": 0.7},
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)
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# (3) The base has collapsed onto the ground.
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fallen_height = DoneTerm(
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func=mdp.root_height_below_minimum,
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params={"minimum_height": 0.08},
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)
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##
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# Environment configuration
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##
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@configclass
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class TwofootbotdemoEnvCfg(ManagerBasedRLEnvCfg):
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scene: TwofootbotdemoSceneCfg = TwofootbotdemoSceneCfg(num_envs=1024, env_spacing=1.5)
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# Basic settings
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observations: ObservationsCfg = ObservationsCfg()
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actions: ActionsCfg = ActionsCfg()
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commands: CommandsCfg = CommandsCfg()
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events: EventCfg = EventCfg()
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# MDP settings
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rewards: RewardsCfg = RewardsCfg()
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terminations: TerminationsCfg = TerminationsCfg()
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# Post initialization
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def __post_init__(self) -> None:
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"""Post initialization."""
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# general settings
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self.decimation = 4
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self.episode_length_s = 20.0
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# viewer settings
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self.viewer.eye = (3.0, 2.5, 1.8)
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# simulation settings
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self.sim.dt = 1 / 200
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self.sim.render_interval = self.decimation
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self.sim.visualizer_cfgs = []
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@ -12,12 +12,51 @@ from . import agents
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##
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gym.register(
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id="Template-Twofootbot-v0",
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'''gym.register(
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id="Template-G1-Twofootbot-mlp-v0",
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entry_point="isaaclab.envs:ManagerBasedRLEnv",
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disable_env_checker=True,
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kwargs={
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"env_cfg_entry_point": f"{__name__}.twofootbot_env_cfg:TwofootbotEnvCfg",
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"env_cfg_entry_point": f"{__name__}.g1_twofootbot_env_cfg:G1RoughEnvCfg",
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"rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:PPORunnerCfg",
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},
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)
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gym.register(
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id="Template-G1-Twofootbot-cnn-v0",
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entry_point="isaaclab.envs:ManagerBasedRLEnv",
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disable_env_checker=True,
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kwargs={
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"env_cfg_entry_point": f"{__name__}.g1_twofootbot_cnn_env_cfg:G1RoughEnvCfg",
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"rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cnn_cfg:PPORunnerCfg",
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},
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)
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gym.register(
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id="Template-G1-Twofootbot-mlp-v0-Play",
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entry_point="isaaclab.envs:ManagerBasedRLEnv",
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disable_env_checker=True,
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kwargs={
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"env_cfg_entry_point": f"{__name__}.g1_twofootbot_env_cfg:G1RoughEnvCfg_PLAY",
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"rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:PPORunnerCfg",
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},
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)
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gym.register(
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id="Template-G1-Twofootbot-cnn-v0-Play",
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entry_point="isaaclab.envs:ManagerBasedRLEnv",
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disable_env_checker=True,
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kwargs={
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"env_cfg_entry_point": f"{__name__}.g1_twofootbot_cnn_env_cfg:G1RoughEnvCfg_PLAY",
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"rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cnn_cfg:PPORunnerCfg",
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},
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)'''
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gym.register(
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id="Template-Twofootbotv0-Demo",
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entry_point="isaaclab.envs:ManagerBasedRLEnv",
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disable_env_checker=True,
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kwargs={
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"env_cfg_entry_point": f"{__name__}.Lv0:TwofootbotdemoEnvCfg",
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"rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:PPORunnerCfg",
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},
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)
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@ -20,8 +20,9 @@ class PPORunnerCfg(RslRlOnPolicyRunnerCfg):
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max_iterations = 5000
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save_interval = 200
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experiment_name = "cartpole_direct"
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obs_groups = {"actor": ["policy", "camera"], "critic": ["policy"]}
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actor = RslRlCNNModelCfg(
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#obs_groups = {"actor": ["policy", "camera"], "critic": ["policy"]}
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obs_groups = {"actor": ["policy"], "critic": ["policy"]}
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'''actor = RslRlCNNModelCfg(
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hidden_dims=[512, 256, 256, 128],
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activation="relu",
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obs_normalization=False,
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@ -32,21 +33,27 @@ class PPORunnerCfg(RslRlOnPolicyRunnerCfg):
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stride=[8,4,2],
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activation="relu",
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),
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)'''
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actor = RslRlMLPModelCfg(
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hidden_dims=[1024, 512, 512, 256, 256, 128], #[1024, 512, 512, 256, 256, 128],
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activation="relu",
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obs_normalization=True,
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distribution_cfg=RslRlMLPModelCfg.GaussianDistributionCfg(init_std=1.0),
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)
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critic = RslRlMLPModelCfg(
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hidden_dims=[1024, 512, 512, 256, 256, 128],
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hidden_dims=[1024, 512, 512, 256, 256, 128], #[1024, 512, 512, 256, 256, 128],
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activation="relu",
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obs_normalization=False,
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obs_normalization=True,
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)
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algorithm = RslRlPpoAlgorithmCfg(
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value_loss_coef=1.0, #价值函数损失系数
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use_clipped_value_loss=True, #是否使用裁剪值损失
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clip_param=0.2, #裁剪参数
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entropy_coef=0.05, #熵系数，探索的奖励
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entropy_coef=0.005, #熵系数，探索的奖励
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num_learning_epochs=5, #学习的轮数
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num_mini_batches=4, #小批量的数量
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learning_rate=5.0e-3, #学习率
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learning_rate=5.0e-4, #学习率
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schedule="adaptive", #学习率调度器类型
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gamma=0.99, #折扣因子
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lam=0.95, #GAE的lambda参数
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@ -0,0 +1,50 @@
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from isaaclab.utils.configclass import configclass
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from isaaclab_rl.rsl_rl import (
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RslRlCNNModelCfg,
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RslRlMLPModelCfg,
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RslRlOnPolicyRunnerCfg,
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RslRlPpoAlgorithmCfg,
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)
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@configclass
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class PPORunnerCfg(RslRlOnPolicyRunnerCfg):
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num_steps_per_env = 16
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max_iterations = 15000
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save_interval = 200
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experiment_name = "cartpole_direct"
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obs_groups = {"actor": ["policy", "camera"], "critic": ["policy"]}
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actor = RslRlCNNModelCfg(
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hidden_dims=[1024, 512, 512, 256, 256, 128],
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activation="relu",
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obs_normalization=False,
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distribution_cfg=RslRlCNNModelCfg.GaussianDistributionCfg(init_std=1.0),
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cnn_cfg=RslRlCNNModelCfg.CNNCfg(
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output_channels=[16,16,16],
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kernel_size=[8, 4, 3],
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stride=[8,4,2],
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activation="relu",
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),
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)
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critic = RslRlMLPModelCfg(
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hidden_dims=[1024, 512, 512, 256, 256, 128], #[1024, 512, 512, 256, 256, 128],
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activation="relu",
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obs_normalization=True,
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)
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algorithm = RslRlPpoAlgorithmCfg(
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value_loss_coef=1.0, #价值函数损失系数
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use_clipped_value_loss=True, #是否使用裁剪值损失
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clip_param=0.2, #裁剪参数
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entropy_coef=0.005, #熵系数，探索的奖励
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num_learning_epochs=5, #学习的轮数
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num_mini_batches=4, #小批量的数量
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learning_rate=5.0e-4, #学习率
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schedule="adaptive", #学习率调度器类型
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gamma=0.99, #折扣因子
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lam=0.95, #GAE的lambda参数
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desired_kl=0.01, #期望的KL散度
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max_grad_norm=1.0, #梯度裁剪的最大范数
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)
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@ -0,0 +1,186 @@
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# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
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||||
# All rights reserved.
|
||||
#
|
||||
# SPDX-License-Identifier: BSD-3-Clause
|
||||
|
||||
|
||||
from isaaclab.managers import RewardTermCfg as RewTerm
|
||||
from isaaclab.managers import SceneEntityCfg
|
||||
from isaaclab.utils.configclass import configclass
|
||||
|
||||
import isaaclab_tasks.manager_based.locomotion.velocity.mdp as mdp
|
||||
from TwoFootBot.tasks.manager_based.twofootbot.twofootbot_cnn_env_cfg import (
|
||||
RewardsCfg,
|
||||
TwofootbotcnnEnvCfg,
|
||||
)
|
||||
|
||||
##
|
||||
# Pre-defined configs
|
||||
##
|
||||
from isaaclab_assets import G1_MINIMAL_CFG # isort: skip
|
||||
|
||||
|
||||
@configclass
|
||||
class G1Rewards(RewardsCfg):
|
||||
|
||||
"""
|
||||
G1机器人的奖励函数配置类，继承自RewardsCfg
|
||||
定义了各种奖励项及其权重，用于训练和评估G1机器人的行为
|
||||
"""
|
||||
# 终止惩罚：当机器人终止时给予的惩罚
|
||||
termination_penalty = RewTerm(func=mdp.is_terminated, weight=-200.0)
|
||||
# 跟踪线性速度奖励：鼓励机器人跟踪期望的xy方向线性速度（在坐标系中）
|
||||
track_lin_vel_xy_exp = RewTerm(
|
||||
func=mdp.track_lin_vel_xy_yaw_frame_exp,
|
||||
weight=1.0,
|
||||
params={"command_name": "base_velocity", "std": 0.5},
|
||||
)
|
||||
# 跟踪角速度奖励：鼓励机器人跟踪期望的z方向角速度（在世界坐标系中）
|
||||
# 奖励项1：跟踪世界坐标系下的z轴角速度期望值
|
||||
track_ang_vel_z_exp = RewTerm(
|
||||
func=mdp.track_ang_vel_z_world_exp, weight=2.0, params={"command_name": "base_velocity", "std": 0.5}
|
||||
)
|
||||
# 定义一个奖励项，用于评估双足机器人的脚部空中时间
|
||||
#feet_air_time_alt = RewTerm(func=feet_air_time_alt, weight=0.0)
|
||||
feet_air_time = RewTerm(
|
||||
func=mdp.feet_air_time_positive_biped, # 调用的函数，用于计算双足机器人脚部空中时间
|
||||
weight=0.25, # 该奖励项的权重，表示在总奖励中的重要性
|
||||
params={ # 函数所需的参数配置
|
||||
"command_name": "base_velocity", # 命令名称，可能与基础速度控制相关
|
||||
"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["lf3_link", "rf3_link"]), # 传感器配置，指定监测接触力的脚部刚体
|
||||
"threshold": 0.4, # 阈值，用于判断脚部是否接触地面
|
||||
},
|
||||
)
|
||||
# 创建一个奖励项(RewTerm)，用于计算脚部滑动惩罚
|
||||
feet_slide = RewTerm(
|
||||
# 指定使用的函数为mdp.feet_slide
|
||||
func=mdp.feet_slide,
|
||||
# 设置权重为-0.1，表示脚部滑动会带来负奖励
|
||||
weight=-0.1,
|
||||
# 配置参数，包括传感器和资产的设置
|
||||
params={
|
||||
# 配置接触力传感器，监测所有脚踝滚动链接的接触力
|
||||
"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["lf3_link", "rf3_link"]),
|
||||
# 配置机器人实体，指定监测所有脚踝滚动链接
|
||||
"asset_cfg": SceneEntityCfg("robot", body_names=["lf3_link", "rf3_link"]),
|
||||
},
|
||||
)
|
||||
|
||||
# 定义一个奖励终端项(Reward Terminal)，用于评估关节位置限制的违反程度
|
||||
dof_pos_limits = RewTerm(
|
||||
# 指定评估函数为mdp.joint_pos_limits，该函数用于计算关节位置限制的违反程度
|
||||
func=mdp.joint_pos_limits,
|
||||
# 设置权重为-1.0，表示当关节位置限制被违反时，会给予负奖励
|
||||
weight=-1.0,
|
||||
#params={"asset_cfg": SceneEntityCfg("robot", joint_names=[])},
|
||||
)
|
||||
# 定义髋关节偏差奖励项
|
||||
joint_deviation_hip = RewTerm(
|
||||
func=mdp.joint_deviation_l1, # 使用L1范数计算关节偏差的函数
|
||||
weight=-0.1, # 奖励权重，负值表示惩罚偏差
|
||||
params={"asset_cfg": SceneEntityCfg("robot", joint_names=["jlf0_link", "jlf1_link", "jrf0_link", "jrf1_link"])}, # 配置参数，指定机器人髋关节的名称模式
|
||||
)
|
||||
|
||||
|
||||
|
||||
@configclass
|
||||
class G1RoughEnvCfg(TwofootbotcnnEnvCfg):
|
||||
"""
|
||||
G1机器人在粗糙环境中的配置类，继承自LocomotionVelocityRoughEnvCfg
|
||||
定义了G1机器人的环境参数、奖励函数、命令范围和终止条件等
|
||||
"""
|
||||
rewards: G1Rewards = G1Rewards()
|
||||
|
||||
def __post_init__(self):
|
||||
# 调用父类的__post_init__方法
|
||||
super().__post_init__()
|
||||
|
||||
|
||||
# 所有髋关节
|
||||
hip_joints = ["jlf0_link", "jrf0_link", "jlf1_link", "jrf1_link"]
|
||||
# ========== 膝关节 ==========
|
||||
knee_joints = ["jlf2_link", "jrf2_link"]
|
||||
|
||||
# ========== 踝关节 ==========
|
||||
ankle_joints = ["jlf3_link", "jrf3_link"]
|
||||
|
||||
|
||||
# 设置基础速度的偏航成功阈值
|
||||
self.commands.base_velocity.vel_yaw_success_threshold = 0.8
|
||||
# 注释：场景中的机器人配置 - 已被注释掉
|
||||
#self.scene.robot = G1_MINIMAL_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
|
||||
# 注释：场景中高度扫描器的路径配置 - 已被注释掉
|
||||
#self.scene.height_scanner.prim_path = "{ENV_REGEX_NS}/Robot/head_link"
|
||||
|
||||
# 初始化事件相关参数
|
||||
self.events.add_base_mass = None
|
||||
#elf.events.base_com = None
|
||||
# 设置外部力矩事件参数，指定作用在机器人躯干链接上
|
||||
self.events.base_external_force_torque.params["asset_cfg"].body_names = "head_link"
|
||||
# 重置机器人关节的位置范围参数
|
||||
self.events.reset_robot_joints.params["position_range"] = (1.0, 1.0)
|
||||
|
||||
|
||||
|
||||
# 设置各种奖励函数的权重
|
||||
self.rewards.lin_vel_z_l2.weight = -0.1 # z方向线速度L2惩罚的权重设为0
|
||||
self.rewards.undesired_contacts = None # 禁用不期望接触的奖励
|
||||
self.rewards.flat_orientation_l2.weight = -1.0 # 平坦方向L2惩罚的权重设为-1.0
|
||||
self.rewards.action_rate_l2.weight = -0.005 # 动作变化率L2惩罚的权重设为-0.005
|
||||
self.rewards.dof_acc_l2.weight = -1.25e-7 # 自由度加速度L2惩罚的权重设为-1.25e-7
|
||||
# 设置自由度加速度L2惩罚的配置参数
|
||||
self.rewards.dof_acc_l2.params["asset_cfg"] = SceneEntityCfg(
|
||||
"robot", joint_names=hip_joints # 只考虑髋关节和膝关节
|
||||
)
|
||||
|
||||
|
||||
# 设置自由度扭矩L2惩罚的权重和配置参数
|
||||
self.rewards.dof_torques_l2.weight = -1.5e-7 # 自由度扭矩L2惩罚的权重设为-1.5e-7
|
||||
self.rewards.dof_torques_l2.params["asset_cfg"] = SceneEntityCfg(
|
||||
"robot", joint_names=hip_joints + knee_joints + ankle_joints # 考虑髋关节、膝关节和踝关节
|
||||
)
|
||||
|
||||
|
||||
|
||||
# 设置基础速度命令的范围
|
||||
self.commands.base_velocity.ranges.lin_vel_x = (0.0, 1.0) # x方向线速度范围设为0到1
|
||||
self.commands.base_velocity.ranges.lin_vel_y = (-0.3, 0.3) # y方向线速度范围设为0（禁止横向移动）
|
||||
self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0) # z方向角速度范围设为-1到1
|
||||
|
||||
|
||||
|
||||
# 设置终止条件的配置参数
|
||||
self.terminations.base_contact.params["sensor_cfg"].body_names = "head_link"
|
||||
# 终止条件基于躯干接触
|
||||
|
||||
@configclass
|
||||
class G1RoughEnvCfg_PLAY(G1RoughEnvCfg):
|
||||
def __post_init__(self):
|
||||
# 调用父类的__post_init__方法
|
||||
super().__post_init__()
|
||||
|
||||
|
||||
|
||||
# 设置场景参数
|
||||
self.scene.num_envs = 50 # 环境数量
|
||||
self.scene.env_spacing = 2.5 # 环境间距
|
||||
self.episode_length_s = 40.0 # 每集长度（秒）
|
||||
self.scene.terrain.max_init_terrain_level = None # 地形最大初始级别设为无限制
|
||||
# 如果地形生成器存在，则设置其参数
|
||||
if self.scene.terrain.terrain_generator is not None:
|
||||
self.scene.terrain.terrain_generator.num_rows = 5 # 地形行数
|
||||
self.scene.terrain.terrain_generator.num_cols = 5 # 地形列数
|
||||
self.scene.terrain.terrain_generator.curriculum = False # 禁用地形课程学习
|
||||
|
||||
|
||||
|
||||
# 设置基础速度命令范围
|
||||
self.commands.base_velocity.ranges.lin_vel_x = (1.0, 1.0) # 前向速度范围（固定值1.0）
|
||||
self.commands.base_velocity.ranges.lin_vel_y = (-0.5, 0.5) # 侧向速度范围（固定值0.0）
|
||||
self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0) # 角速度范围（-1.0到1.0）
|
||||
self.commands.base_velocity.ranges.heading = (0.0, 0.0) # 朝向范围（固定值0.0）
|
||||
# 禁用策略观察值的损坏
|
||||
self.observations.policy.enable_corruption = False
|
||||
# 禁用外部力和推力事件
|
||||
self.events.base_external_force_torque = None
|
||||
self.events.push_robot = None
|
||||
|
|
@ -0,0 +1,186 @@
|
|||
# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
|
||||
# All rights reserved.
|
||||
#
|
||||
# SPDX-License-Identifier: BSD-3-Clause
|
||||
|
||||
|
||||
from isaaclab.managers import RewardTermCfg as RewTerm
|
||||
from isaaclab.managers import SceneEntityCfg
|
||||
from isaaclab.utils.configclass import configclass
|
||||
|
||||
import isaaclab_tasks.manager_based.locomotion.velocity.mdp as mdp
|
||||
from TwoFootBot.tasks.manager_based.twofootbot.velocity_env_cfg import (
|
||||
RewardsCfg,
|
||||
LocomotionVelocityRoughEnvCfg,
|
||||
)
|
||||
|
||||
##
|
||||
# Pre-defined configs
|
||||
##
|
||||
from isaaclab_assets import G1_MINIMAL_CFG # isort: skip
|
||||
|
||||
|
||||
@configclass
|
||||
class G1Rewards(RewardsCfg):
|
||||
|
||||
"""
|
||||
G1机器人的奖励函数配置类，继承自RewardsCfg
|
||||
定义了各种奖励项及其权重，用于训练和评估G1机器人的行为
|
||||
"""
|
||||
# 终止惩罚：当机器人终止时给予的惩罚
|
||||
termination_penalty = RewTerm(func=mdp.is_terminated, weight=-200.0)
|
||||
# 跟踪线性速度奖励：鼓励机器人跟踪期望的xy方向线性速度（在坐标系中）
|
||||
track_lin_vel_xy_exp = RewTerm(
|
||||
func=mdp.track_lin_vel_xy_yaw_frame_exp,
|
||||
weight=1.0,
|
||||
params={"command_name": "base_velocity", "std": 0.5},
|
||||
)
|
||||
# 跟踪角速度奖励：鼓励机器人跟踪期望的z方向角速度（在世界坐标系中）
|
||||
# 奖励项1：跟踪世界坐标系下的z轴角速度期望值
|
||||
track_ang_vel_z_exp = RewTerm(
|
||||
func=mdp.track_ang_vel_z_world_exp, weight=2.0, params={"command_name": "base_velocity", "std": 0.5}
|
||||
)
|
||||
# 定义一个奖励项，用于评估双足机器人的脚部空中时间
|
||||
#feet_air_time_alt = RewTerm(func=feet_air_time_alt, weight=0.0)
|
||||
feet_air_time = RewTerm(
|
||||
func=mdp.feet_air_time_positive_biped, # 调用的函数，用于计算双足机器人脚部空中时间
|
||||
weight=0.25, # 该奖励项的权重，表示在总奖励中的重要性
|
||||
params={ # 函数所需的参数配置
|
||||
"command_name": "base_velocity", # 命令名称，可能与基础速度控制相关
|
||||
"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["lf3_link", "rf3_link"]), # 传感器配置，指定监测接触力的脚部刚体
|
||||
"threshold": 0.4, # 阈值，用于判断脚部是否接触地面
|
||||
},
|
||||
)
|
||||
# 创建一个奖励项(RewTerm)，用于计算脚部滑动惩罚
|
||||
feet_slide = RewTerm(
|
||||
# 指定使用的函数为mdp.feet_slide
|
||||
func=mdp.feet_slide,
|
||||
# 设置权重为-0.1，表示脚部滑动会带来负奖励
|
||||
weight=-0.1,
|
||||
# 配置参数，包括传感器和资产的设置
|
||||
params={
|
||||
# 配置接触力传感器，监测所有脚踝滚动链接的接触力
|
||||
"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["lf3_link", "rf3_link"]),
|
||||
# 配置机器人实体，指定监测所有脚踝滚动链接
|
||||
"asset_cfg": SceneEntityCfg("robot", body_names=["lf3_link", "rf3_link"]),
|
||||
},
|
||||
)
|
||||
|
||||
# 定义一个奖励终端项(Reward Terminal)，用于评估关节位置限制的违反程度
|
||||
dof_pos_limits = RewTerm(
|
||||
# 指定评估函数为mdp.joint_pos_limits，该函数用于计算关节位置限制的违反程度
|
||||
func=mdp.joint_pos_limits,
|
||||
# 设置权重为-1.0，表示当关节位置限制被违反时，会给予负奖励
|
||||
weight=-1.0,
|
||||
#params={"asset_cfg": SceneEntityCfg("robot", joint_names=[])},
|
||||
)
|
||||
# 定义髋关节偏差奖励项
|
||||
joint_deviation_hip = RewTerm(
|
||||
func=mdp.joint_deviation_l1, # 使用L1范数计算关节偏差的函数
|
||||
weight=-0.1, # 奖励权重，负值表示惩罚偏差
|
||||
params={"asset_cfg": SceneEntityCfg("robot", joint_names=["jlf0_link", "jlf1_link", "jrf0_link", "jrf1_link"])}, # 配置参数，指定机器人髋关节的名称模式
|
||||
)
|
||||
|
||||
|
||||
|
||||
@configclass
|
||||
class G1RoughEnvCfg(LocomotionVelocityRoughEnvCfg):
|
||||
"""
|
||||
G1机器人在粗糙环境中的配置类，继承自LocomotionVelocityRoughEnvCfg
|
||||
定义了G1机器人的环境参数、奖励函数、命令范围和终止条件等
|
||||
"""
|
||||
rewards: G1Rewards = G1Rewards()
|
||||
|
||||
def __post_init__(self):
|
||||
# 调用父类的__post_init__方法
|
||||
super().__post_init__()
|
||||
|
||||
|
||||
# 所有髋关节
|
||||
hip_joints = ["jlf0_link", "jrf0_link", "jlf1_link", "jrf1_link"]
|
||||
# ========== 膝关节 ==========
|
||||
knee_joints = ["jlf2_link", "jrf2_link"]
|
||||
|
||||
# ========== 踝关节 ==========
|
||||
ankle_joints = ["jlf3_link", "jrf3_link"]
|
||||
|
||||
|
||||
# 设置基础速度的偏航成功阈值
|
||||
self.commands.base_velocity.vel_yaw_success_threshold = 0.8
|
||||
# 注释：场景中的机器人配置 - 已被注释掉
|
||||
#self.scene.robot = G1_MINIMAL_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
|
||||
# 注释：场景中高度扫描器的路径配置 - 已被注释掉
|
||||
#self.scene.height_scanner.prim_path = "{ENV_REGEX_NS}/Robot/head_link"
|
||||
|
||||
# 初始化事件相关参数
|
||||
self.events.add_base_mass = None
|
||||
#elf.events.base_com = None
|
||||
# 设置外部力矩事件参数，指定作用在机器人躯干链接上
|
||||
self.events.base_external_force_torque.params["asset_cfg"].body_names = "head_link"
|
||||
# 重置机器人关节的位置范围参数
|
||||
self.events.reset_robot_joints.params["position_range"] = (1.0, 1.0)
|
||||
|
||||
|
||||
|
||||
# 设置各种奖励函数的权重
|
||||
self.rewards.lin_vel_z_l2.weight = -0.1 # z方向线速度L2惩罚的权重设为0
|
||||
self.rewards.undesired_contacts = None # 禁用不期望接触的奖励
|
||||
self.rewards.flat_orientation_l2.weight = -1.0 # 平坦方向L2惩罚的权重设为-1.0
|
||||
self.rewards.action_rate_l2.weight = -0.005 # 动作变化率L2惩罚的权重设为-0.005
|
||||
self.rewards.dof_acc_l2.weight = -1.25e-7 # 自由度加速度L2惩罚的权重设为-1.25e-7
|
||||
# 设置自由度加速度L2惩罚的配置参数
|
||||
self.rewards.dof_acc_l2.params["asset_cfg"] = SceneEntityCfg(
|
||||
"robot", joint_names=hip_joints # 只考虑髋关节和膝关节
|
||||
)
|
||||
|
||||
|
||||
# 设置自由度扭矩L2惩罚的权重和配置参数
|
||||
self.rewards.dof_torques_l2.weight = -1.5e-7 # 自由度扭矩L2惩罚的权重设为-1.5e-7
|
||||
self.rewards.dof_torques_l2.params["asset_cfg"] = SceneEntityCfg(
|
||||
"robot", joint_names=hip_joints + knee_joints + ankle_joints # 考虑髋关节、膝关节和踝关节
|
||||
)
|
||||
|
||||
|
||||
|
||||
# 设置基础速度命令的范围
|
||||
self.commands.base_velocity.ranges.lin_vel_x = (0.0, 1.0) # x方向线速度范围设为0到1
|
||||
self.commands.base_velocity.ranges.lin_vel_y = (-0.3, 0.3) # y方向线速度范围设为0（禁止横向移动）
|
||||
self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0) # z方向角速度范围设为-1到1
|
||||
|
||||
|
||||
|
||||
# 设置终止条件的配置参数
|
||||
self.terminations.base_contact.params["sensor_cfg"].body_names = "head_link"
|
||||
# 终止条件基于躯干接触
|
||||
|
||||
@configclass
|
||||
class G1RoughEnvCfg_PLAY(G1RoughEnvCfg):
|
||||
def __post_init__(self):
|
||||
# 调用父类的__post_init__方法
|
||||
super().__post_init__()
|
||||
|
||||
|
||||
|
||||
# 设置场景参数
|
||||
self.scene.num_envs = 50 # 环境数量
|
||||
self.scene.env_spacing = 2.5 # 环境间距
|
||||
self.episode_length_s = 40.0 # 每集长度（秒）
|
||||
self.scene.terrain.max_init_terrain_level = None # 地形最大初始级别设为无限制
|
||||
# 如果地形生成器存在，则设置其参数
|
||||
if self.scene.terrain.terrain_generator is not None:
|
||||
self.scene.terrain.terrain_generator.num_rows = 5 # 地形行数
|
||||
self.scene.terrain.terrain_generator.num_cols = 5 # 地形列数
|
||||
self.scene.terrain.terrain_generator.curriculum = False # 禁用地形课程学习
|
||||
|
||||
|
||||
|
||||
# 设置基础速度命令范围
|
||||
self.commands.base_velocity.ranges.lin_vel_x = (1.0, 1.0) # 前向速度范围（固定值1.0）
|
||||
self.commands.base_velocity.ranges.lin_vel_y = (-0.5, 0.5) # 侧向速度范围（固定值0.0）
|
||||
self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0) # 角速度范围（-1.0到1.0）
|
||||
self.commands.base_velocity.ranges.heading = (0.0, 0.0) # 朝向范围（固定值0.0）
|
||||
# 禁用策略观察值的损坏
|
||||
self.observations.policy.enable_corruption = False
|
||||
# 禁用外部力和推力事件
|
||||
self.events.base_external_force_torque = None
|
||||
self.events.push_robot = None
|
||||
|
|
@ -236,11 +236,36 @@ JOINT_NAMES = [ # 定义机器人需要控制的八个关节名称。
|
|||
BOT_PACKAGE_PATH = Path(__file__).resolve().parents[6] / "bot/2foot" # 获取机器人 ROS 包目录。
|
||||
URDF_PATH = BOT_PACKAGE_PATH / "urdf/2foot.urdf" # 指定正式使用的 2foot URDF 文件。
|
||||
|
||||
def spawn_twofootbot_from_urdf(prim_path, cfg, translation=None, orientation=None, **kwargs):
|
||||
"""Spawn the URDF and enable contact reporting on every rigid link."""
|
||||
from pxr import Usd, UsdPhysics
|
||||
from isaaclab.sim.spawners.from_files.from_files import spawn_from_urdf
|
||||
from isaaclab.sim.utils import safe_set_attribute_on_usd_prim
|
||||
|
||||
spawn_cfg = cfg.replace(activate_contact_sensors=False)
|
||||
prim = spawn_from_urdf(prim_path, spawn_cfg, translation, orientation, **kwargs)
|
||||
for child_prim in Usd.PrimRange(prim):
|
||||
if not child_prim.HasAPI(UsdPhysics.RigidBodyAPI):
|
||||
continue
|
||||
applied_schemas = child_prim.GetAppliedSchemas()
|
||||
if "PhysxRigidBodyAPI" not in applied_schemas:
|
||||
child_prim.AddAppliedSchema("PhysxRigidBodyAPI")
|
||||
if "PhysxContactReportAPI" not in applied_schemas:
|
||||
child_prim.AddAppliedSchema("PhysxContactReportAPI")
|
||||
safe_set_attribute_on_usd_prim(
|
||||
child_prim, "physxRigidBody:sleepThreshold", 0.0, camel_case=False
|
||||
)
|
||||
safe_set_attribute_on_usd_prim(
|
||||
child_prim, "physxContactReport:threshold", 0.0, camel_case=False
|
||||
)
|
||||
return prim
|
||||
|
||||
TOFOOTBOT_CFG = ArticulationCfg(
|
||||
spawn=sim_utils.UrdfFileCfg(
|
||||
func=spawn_twofootbot_from_urdf,
|
||||
asset_path=str(URDF_PATH),
|
||||
fix_base=False,
|
||||
activate_contact_sensors=True,
|
||||
activate_contact_sensors=False,
|
||||
ros_package_paths=[{"name": "2foot", "path": str(BOT_PACKAGE_PATH)}],
|
||||
joint_drive=sim_utils.UrdfFileCfg.JointDriveCfg(
|
||||
drive_type="force",
|
||||
|
|
@ -268,7 +293,8 @@ TOFOOTBOT_CFG = ArticulationCfg(
|
|||
actuators={ # 动力配置。
|
||||
"legs": ImplicitActuatorCfg(
|
||||
joint_names_expr=JOINT_NAMES, # 控制所有腿的关节。
|
||||
effort_limit_sim=0.08, # 力矩限制。单位：牛顿米。
|
||||
effort_limit_sim=10, # 力矩限制。单位：牛顿米。
|
||||
velocity_limit_sim=8.0554, # 速度限制 (rad/s)
|
||||
stiffness=2.0, # 刚度。单位：牛顿/米。
|
||||
damping=0.08, # 阻尼。单位：牛顿秒/米。
|
||||
)
|
||||
|
|
@ -365,15 +391,15 @@ class MySceneCfg(InteractiveSceneCfg):
|
|||
# robots
|
||||
robot: ArticulationCfg = TOFOOTBOT_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
|
||||
# sensors
|
||||
#height_scanner = None
|
||||
height_scanner = RayCasterCfg(
|
||||
height_scanner = None
|
||||
'''height_scanner = RayCasterCfg(
|
||||
prim_path="{ENV_REGEX_NS}/Robot/head_link",
|
||||
offset=RayCasterCfg.OffsetCfg(pos=(0.0, 0.0, 20.0)),
|
||||
ray_alignment="yaw",
|
||||
pattern_cfg=patterns.GridPatternCfg(resolution=0.1, size=[0.40, 0.25]),
|
||||
debug_vis=False,
|
||||
mesh_prim_paths=["/World/ground"],
|
||||
)
|
||||
)'''
|
||||
contact_forces = VelocityEnvContactSensorCfg()
|
||||
|
||||
# lights
|
||||
|
|
@ -404,7 +430,7 @@ class CommandsCfg:
|
|||
heading_control_stiffness=0.5,
|
||||
debug_vis=True,
|
||||
ranges=mdp.UniformVelocityCommandCfg.Ranges(
|
||||
lin_vel_x=(-0.5, 0.5), lin_vel_y=(-0.3, 0.3), ang_vel_z=(-0.5, 0.5), heading=(-math.pi, math.pi)
|
||||
lin_vel_x=(-1.0, 1.0), lin_vel_y=(-1.0, 1.0), ang_vel_z=(-1.0, 1.0), heading=(-math.pi, math.pi)
|
||||
),
|
||||
)
|
||||
|
||||
|
|
@ -559,23 +585,6 @@ class EventsCfg:
|
|||
)
|
||||
|
||||
|
||||
def feet_air_time_alt(env):
|
||||
"""替代奖励：基于足端高度估计空中时间，鼓励足部腾空。"""
|
||||
# 获取左右足端位置（世界坐标）
|
||||
foot_l_pos = env.scene["robot"].data.body_pos_w[:, env.scene["robot"].body_names.index("lf3_link")]
|
||||
foot_r_pos = env.scene["robot"].data.body_pos_w[:, env.scene["robot"].body_names.index("rf3_link")]
|
||||
foot_z = torch.stack([foot_l_pos[:, 2], foot_r_pos[:, 2]], dim=1) # (num_envs, 2)
|
||||
|
||||
# 触地判断（高度低于阈值）
|
||||
contact_threshold = 0.02 # 可根据机器人尺寸调整
|
||||
in_air = foot_z > contact_threshold # True表示在空中
|
||||
|
||||
# 计算每只脚累计空中步数（可在环境状态中存储历史）
|
||||
# 这里简化：给予即时奖励：空中高度*系数
|
||||
#air_time_reward = torch.sum(foot_z * in_air.float(), dim=1) * 1 # 系数可调
|
||||
air_time_reward = torch.sum(in_air.float(), dim=1) * 1 # 每只脚在空中给予奖励
|
||||
return air_time_reward
|
||||
|
||||
@configclass
|
||||
class RewardsCfg:
|
||||
"""Reward terms for the MDP."""
|
||||
|
|
@ -593,37 +602,25 @@ class RewardsCfg:
|
|||
dof_torques_l2 = RewTerm(func=mdp.joint_torques_l2, weight=-1.0e-5)#关节力矩平方和
|
||||
dof_acc_l2 = RewTerm(func=mdp.joint_acc_l2, weight=-2.5e-7)#关节加速度平方和
|
||||
action_rate_l2 = RewTerm(func=mdp.action_rate_l2, weight=-1.0e-3)#惩罚相邻动作之间的变化量平方
|
||||
alive = RewTerm( #固定时间惩罚
|
||||
func=mdp.is_alive, # 该函数通常返回1（若机器人存活）
|
||||
weight=-0.25,
|
||||
)
|
||||
fall_penalty = RewTerm( #摔倒惩罚
|
||||
func=mdp.is_terminated_term,
|
||||
weight=-100.0,
|
||||
params={"term_keys": "base_contact"},
|
||||
)
|
||||
|
||||
feet_air_time_alt = RewTerm(func=feet_air_time_alt, weight=0.1) # 足端空中时间奖励
|
||||
#feet_air_time_alt = RewTerm(func=feet_air_time_alt, weight=0.1) # 足端空中时间奖励
|
||||
|
||||
'''feet_air_time = RewTerm(
|
||||
feet_air_time = RewTerm(
|
||||
func=mdp.feet_air_time,
|
||||
weight=0.125,
|
||||
params={
|
||||
#"sensor_cfg": SceneEntityCfg("contact_forces", body_names=".*3_link"),
|
||||
"sensor_cfg": SceneEntityCfg("robot", body_names=".*3_link"),
|
||||
"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["lf3_link", "rf3_link"]),
|
||||
"command_name": "base_velocity",
|
||||
"threshold": 0.5,
|
||||
},
|
||||
)
|
||||
# 定义一个不期望接触的惩罚项，用于优化机器人运动
|
||||
# 使用RewTerm类创建，其权重为负值，表示对不期望接触的行为进行惩罚
|
||||
undesired_contacts = RewTerm(
|
||||
func=mdp.undesired_contacts,
|
||||
weight=-1.0,
|
||||
params={
|
||||
#"sensor_cfg": SceneEntityCfg("contact_forces", body_names=".*0_link"),
|
||||
"sensor_cfg": SceneEntityCfg("robot", body_names=".*0_link"),
|
||||
"threshold": 1.0
|
||||
},
|
||||
)'''
|
||||
func=mdp.undesired_contacts, # 指定使用的函数mdp.undesired_contacts，用于计算不期望接触的惩罚
|
||||
weight=-1.0, # 设置权重为-1.0，表示不期望接触的行为会带来负奖励
|
||||
params={"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["head_link", "lf0_link", "rf0_link"]), "threshold": 1.0},
|
||||
)
|
||||
|
||||
# -- optional penalties
|
||||
flat_orientation_l2 = RewTerm(func=mdp.flat_orientation_l2, weight=-1.5) #惩罚倾斜角度
|
||||
|
|
@ -636,8 +633,11 @@ class TerminationsCfg:
|
|||
time_out = DoneTerm(func=mdp.time_out, time_out=True)
|
||||
base_contact = DoneTerm(
|
||||
func=mdp.illegal_contact,
|
||||
params={"sensor_cfg": SceneEntityCfg("contact_forces", body_names="head_link"), "threshold": 1.0},
|
||||
#params={"asset_cfg": SceneEntityCfg("robot", body_names=["head_link", "lf0_link", "rf0_link"]), "threshold": 1.0},
|
||||
params={"sensor_cfg": SceneEntityCfg("contact_forces", body_names=[
|
||||
"head_link",
|
||||
"lf0_link", "lf1_link", "lf2_link",
|
||||
"rf0_link", "rf1_link", "rf2_link",
|
||||
]), "threshold": 1.0},
|
||||
)
|
||||
#机器人Z轴与世界Z轴夹角超90度则终止
|
||||
'''upside_down = DoneTerm(
|
||||
|
|
@ -649,7 +649,8 @@ class TerminationsCfg:
|
|||
class CurriculumCfg:
|
||||
"""Curriculum terms for the MDP."""
|
||||
|
||||
terrain_levels = CurrTerm(func=mdp.terrain_levels_vel)
|
||||
# The scene uses a flat plane, so there is no terrain generator to update.
|
||||
terrain_levels = None
|
||||
|
||||
|
||||
##
|
||||
|
|
@ -658,7 +659,7 @@ class CurriculumCfg:
|
|||
|
||||
|
||||
@configclass
|
||||
class TwofootbotEnvCfg(ManagerBasedRLEnvCfg):
|
||||
class TwofootbotcnnEnvCfg(ManagerBasedRLEnvCfg):
|
||||
"""Configuration for the locomotion velocity-tracking environment."""
|
||||
|
||||
# Simulation settings — shared physics preset (PhysX + MJWarp) for all rough-terrain envs
|
||||
|
|
@ -0,0 +1,578 @@
|
|||
# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
|
||||
# All rights reserved.
|
||||
#
|
||||
# SPDX-License-Identifier: BSD-3-Clause
|
||||
|
||||
import math
|
||||
from dataclasses import MISSING
|
||||
from pathlib import Path
|
||||
import torch
|
||||
from isaaclab.sensors import ContactSensorCfg
|
||||
from isaaclab_newton.physics import MJWarpSolverCfg, NewtonCfg, NewtonCollisionPipelineCfg, NewtonShapeCfg
|
||||
from isaaclab_newton.sensors import ContactSensorCfg as NewtonContactSensorCfg
|
||||
from isaaclab_ovphysx.sensors import ContactSensorCfg as OvPhysXContactSensorCfg
|
||||
from isaaclab_physx.physics import PhysxCfg
|
||||
from isaaclab_physx.sensors import ContactSensorCfg as PhysXContactSensorCfg
|
||||
|
||||
from isaaclab.actuators import ImplicitActuatorCfg
|
||||
|
||||
import isaaclab.sim as sim_utils
|
||||
from isaaclab.assets import ArticulationCfg, AssetBaseCfg
|
||||
from isaaclab.envs import ManagerBasedRLEnvCfg
|
||||
from isaaclab.managers import CurriculumTermCfg as CurrTerm
|
||||
from isaaclab.managers import EventTermCfg as EventTerm
|
||||
from isaaclab.managers import ObservationGroupCfg as ObsGroup
|
||||
from isaaclab.managers import ObservationTermCfg as ObsTerm
|
||||
from isaaclab.managers import RewardTermCfg as RewTerm
|
||||
from isaaclab.managers import SceneEntityCfg
|
||||
from isaaclab.managers import TerminationTermCfg as DoneTerm
|
||||
from isaaclab.scene import InteractiveSceneCfg
|
||||
from isaaclab.sensors import RayCasterCfg, patterns
|
||||
from isaaclab.sim import SimulationCfg
|
||||
from isaaclab.terrains import TerrainImporterCfg
|
||||
from isaaclab.utils.assets import ISAAC_NUCLEUS_DIR, ISAACLAB_NUCLEUS_DIR
|
||||
from isaaclab.utils.configclass import configclass
|
||||
from isaaclab.utils.noise import UniformNoiseCfg as Unoise
|
||||
|
||||
import isaaclab_tasks.manager_based.locomotion.velocity.mdp as mdp
|
||||
#from isaaclab.managers import mdp as base_mdp
|
||||
from isaaclab_tasks.utils import PresetCfg, preset
|
||||
|
||||
from isaaclab.sensors import CameraCfg
|
||||
from isaaclab.sensors import TiledCameraCfg
|
||||
from isaaclab.sim import PinholeCameraCfg
|
||||
|
||||
|
||||
import isaaclab.sim as sim_utils
|
||||
from isaaclab.actuators import ImplicitActuatorCfg
|
||||
from isaaclab.assets import ArticulationCfg
|
||||
|
||||
from isaaclab.managers import (
|
||||
RewardTermCfg,
|
||||
TerminationTermCfg,
|
||||
EventTermCfg as EventTerm,
|
||||
ObservationGroupCfg as ObsGroup,
|
||||
ObservationTermCfg as ObsTerm,
|
||||
CurriculumTermCfg as CurriculumTerm,
|
||||
SceneEntityCfg,
|
||||
)
|
||||
|
||||
|
||||
JOINT_NAMES = [ # 定义机器人需要控制的八个关节名称。
|
||||
"jlf0_link",
|
||||
"jlf1_link",
|
||||
"jlf2_link",
|
||||
"jlf3_link",
|
||||
"jrf0_link",
|
||||
"jrf1_link",
|
||||
"jrf2_link",
|
||||
"jrf3_link",
|
||||
]
|
||||
BOT_PACKAGE_PATH = Path(__file__).resolve().parents[6] / "bot/2foot" # 获取机器人 ROS 包目录。
|
||||
URDF_PATH = BOT_PACKAGE_PATH / "urdf/2foot.urdf" # 指定正式使用的 2foot URDF 文件。
|
||||
|
||||
|
||||
URDF_PATH = "/home/zhenai/AI/RL/bot/2foot/urdf/2foot.urdf"
|
||||
BOT_PACKAGE_PATH = "/home/zhenai/AI/RL/bot/2foot" # ⚠️ 确保这个目录下有 meshes/ 文件夹
|
||||
|
||||
|
||||
def spawn_twofootbot_from_urdf(prim_path, cfg, translation=None, orientation=None, **kwargs):
|
||||
"""Spawn the URDF and enable contact reporting on every rigid link."""
|
||||
from pxr import Usd, UsdPhysics
|
||||
from isaaclab.sim.spawners.from_files.from_files import spawn_from_urdf
|
||||
from isaaclab.sim.utils import safe_set_attribute_on_usd_prim
|
||||
|
||||
spawn_cfg = cfg.replace(activate_contact_sensors=False)
|
||||
prim = spawn_from_urdf(prim_path, spawn_cfg, translation, orientation, **kwargs)
|
||||
for child_prim in Usd.PrimRange(prim):
|
||||
if child_prim.HasAPI(UsdPhysics.RigidBodyAPI):
|
||||
applied_schemas = child_prim.GetAppliedSchemas()
|
||||
if "PhysxRigidBodyAPI" not in applied_schemas:
|
||||
child_prim.AddAppliedSchema("PhysxRigidBodyAPI")
|
||||
if "PhysxContactReportAPI" not in applied_schemas:
|
||||
child_prim.AddAppliedSchema("PhysxContactReportAPI")
|
||||
safe_set_attribute_on_usd_prim(
|
||||
child_prim, "physxRigidBody:sleepThreshold", 0.0, camel_case=False
|
||||
)
|
||||
safe_set_attribute_on_usd_prim(
|
||||
child_prim, "physxContactReport:threshold", 0.0, camel_case=False
|
||||
)
|
||||
return prim
|
||||
|
||||
|
||||
# 双足机器人URDF配置对象
|
||||
TWOFOOTBOT_URDF_CFG = ArticulationCfg(
|
||||
# 配置双足机器人从URDF文件生成
|
||||
spawn=sim_utils.UrdfFileCfg(
|
||||
# 指定用于生成机器人的函数
|
||||
func=spawn_twofootbot_from_urdf,
|
||||
asset_path=URDF_PATH,
|
||||
# 设置参数：是否固定基座
|
||||
fix_base=False,
|
||||
# 设置参数：是否激活接触传感器
|
||||
activate_contact_sensors=False,
|
||||
# ROS包路径配置
|
||||
ros_package_paths=[{"name": "2foot", "path": BOT_PACKAGE_PATH}],
|
||||
# 关节驱动配置
|
||||
# 创建一个关节驱动配置，使用URDF文件配置中的JointDriveCfg类
|
||||
joint_drive=sim_utils.UrdfFileCfg.JointDriveCfg(
|
||||
# 设置驱动类型为"force"，表示通过力来控制关节
|
||||
drive_type="force",
|
||||
# 设置目标类型为"position"，表示目标是控制关节位置
|
||||
target_type="position",
|
||||
# 设置控制增益参数，使用PD控制器配置
|
||||
gains=sim_utils.UrdfFileCfg.JointDriveCfg.PDGainsCfg(
|
||||
stiffness=17,
|
||||
damping=0
|
||||
),
|
||||
),
|
||||
# 刚体属性配置
|
||||
rigid_props=sim_utils.RigidBodyPropertiesCfg(
|
||||
disable_gravity=False,
|
||||
max_linear_velocity=100.0,
|
||||
max_angular_velocity=100.0,
|
||||
max_depenetration_velocity=5.0,
|
||||
),
|
||||
# 关节属性配置
|
||||
articulation_props=sim_utils.ArticulationRootPropertiesCfg(
|
||||
enabled_self_collisions=False,
|
||||
solver_position_iteration_count=4,
|
||||
solver_velocity_iteration_count=0,
|
||||
),
|
||||
),
|
||||
# 初始状态配置
|
||||
init_state=ArticulationCfg.InitialStateCfg(
|
||||
pos=(0.0, 0.0, 0.22),
|
||||
joint_pos={
|
||||
"jlf0_link": 0.0, "jlf1_link": 0.0, "jlf2_link": 0.0, "jlf3_link": 0.0,
|
||||
"jrf0_link": 0.0, "jrf1_link": 0.0, "jrf2_link": 0.0, "jrf3_link": 0.0,
|
||||
},
|
||||
joint_vel={".*": 0.0},
|
||||
),
|
||||
# 执行器配置
|
||||
actuators={
|
||||
"legs": ImplicitActuatorCfg(
|
||||
# 关节名称表达式列表
|
||||
joint_names_expr=[
|
||||
"jlf0_link", "jlf1_link", "jlf2_link", "jlf3_link",
|
||||
"jrf0_link", "jrf1_link", "jrf2_link", "jrf3_link",
|
||||
],
|
||||
# 仿真中的力限制
|
||||
effort_limit_sim=0.5,
|
||||
# 仿真中的速度限制
|
||||
velocity_limit_sim=5.0, # 速度限制 (rad/s)
|
||||
# 刚度系数
|
||||
stiffness=5,
|
||||
# 阻尼系数
|
||||
damping=0.3,
|
||||
)
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
##
|
||||
# Physics presets
|
||||
##
|
||||
|
||||
|
||||
@configclass
|
||||
class RoughPhysicsCfg(PresetCfg):
|
||||
"""Shared physics preset for all rough-terrain locomotion envs."""
|
||||
|
||||
default = PhysxCfg(gpu_max_rigid_patch_count=10 * 2**15)
|
||||
newton_mjwarp = NewtonCfg(
|
||||
solver_cfg=MJWarpSolverCfg(
|
||||
njmax=200,
|
||||
nconmax=100,
|
||||
cone="pyramidal",
|
||||
impratio=1.0,
|
||||
integrator="implicitfast",
|
||||
use_mujoco_contacts=False,
|
||||
),
|
||||
collision_cfg=NewtonCollisionPipelineCfg(max_triangle_pairs=2_500_000),
|
||||
num_substeps=1,
|
||||
debug_mode=False,
|
||||
# 1 cm shape margin is the single most important Newton setting for rough
|
||||
# terrain — without it, non-Anymal-D robots fail to learn stable contact
|
||||
# on triangle-mesh terrain. See isaaclab_newton 0.5.22 changelog.
|
||||
default_shape_cfg=NewtonShapeCfg(margin=0.01),
|
||||
)
|
||||
physx = default
|
||||
|
||||
|
||||
##
|
||||
# Scene definition
|
||||
##
|
||||
|
||||
|
||||
@configclass
|
||||
class VelocityEnvContactSensorCfg(PresetCfg):
|
||||
default = PhysXContactSensorCfg(prim_path="{ENV_REGEX_NS}/Robot/.*", history_length=3, track_air_time=True)
|
||||
newton_mjwarp = NewtonContactSensorCfg(prim_path="{ENV_REGEX_NS}/Robot/.*", history_length=3, track_air_time=True)
|
||||
physx = default
|
||||
ovphysx = OvPhysXContactSensorCfg(prim_path="{ENV_REGEX_NS}/Robot/.*", history_length=3, track_air_time=True)
|
||||
|
||||
|
||||
@configclass
|
||||
class MySceneCfg(InteractiveSceneCfg):
|
||||
"""Configuration for the terrain scene with a legged robot."""
|
||||
|
||||
# ground terrain
|
||||
terrain = TerrainImporterCfg(
|
||||
prim_path="/World/ground",
|
||||
terrain_type="plane",
|
||||
collision_group=-1,
|
||||
physics_material=sim_utils.RigidBodyMaterialCfg(
|
||||
friction_combine_mode="multiply",
|
||||
restitution_combine_mode="multiply",
|
||||
static_friction=1.0,
|
||||
dynamic_friction=1.0,
|
||||
),
|
||||
visual_material=sim_utils.MdlFileCfg(
|
||||
mdl_path=f"{ISAACLAB_NUCLEUS_DIR}/Materials/TilesMarbleSpiderWhiteBrickBondHoned/TilesMarbleSpiderWhiteBrickBondHoned.mdl",
|
||||
project_uvw=True,
|
||||
texture_scale=(0.25, 0.25),
|
||||
),
|
||||
debug_vis=False,
|
||||
)
|
||||
# robots
|
||||
robot: ArticulationCfg = TWOFOOTBOT_URDF_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
|
||||
# sensors
|
||||
height_scanner = None
|
||||
'''height_scanner = RayCasterCfg(
|
||||
prim_path="{ENV_REGEX_NS}/Robot/head_link",
|
||||
offset=RayCasterCfg.OffsetCfg(pos=(0.0, 0.0, 20.0)),
|
||||
ray_alignment="yaw",
|
||||
pattern_cfg=patterns.GridPatternCfg(resolution=0.1, size=[1.6, 1.0]),
|
||||
debug_vis=False,
|
||||
mesh_prim_paths=["/World/ground"],
|
||||
)'''
|
||||
contact_forces = VelocityEnvContactSensorCfg()
|
||||
# lights
|
||||
sky_light = AssetBaseCfg(
|
||||
prim_path="/World/skyLight",
|
||||
spawn=sim_utils.DomeLightCfg(
|
||||
intensity=750.0,
|
||||
texture_file=f"{ISAAC_NUCLEUS_DIR}/Materials/Textures/Skies/PolyHaven/kloofendal_43d_clear_puresky_4k.hdr",
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
##
|
||||
# MDP settings
|
||||
##
|
||||
|
||||
|
||||
@configclass
|
||||
class CommandsCfg:
|
||||
"""Command specifications for the MDP."""
|
||||
|
||||
base_velocity = mdp.UniformVelocityCommandCfg(
|
||||
asset_name="robot",
|
||||
resampling_time_range=(10.0, 10.0),
|
||||
rel_standing_envs=0.02,
|
||||
rel_heading_envs=1.0,
|
||||
heading_command=True,
|
||||
heading_control_stiffness=0.5,
|
||||
debug_vis=True,
|
||||
ranges=mdp.UniformVelocityCommandCfg.Ranges(
|
||||
lin_vel_x=(-1.0, 1.0), lin_vel_y=(-1.0, 1.0), ang_vel_z=(-1.0, 1.0), heading=(-math.pi, math.pi)
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
@configclass
|
||||
class ActionsCfg:
|
||||
"""Action specifications for the MDP."""
|
||||
|
||||
joint_pos = mdp.JointPositionActionCfg(asset_name="robot", joint_names=[".*"], scale=0.5, use_default_offset=True)
|
||||
|
||||
|
||||
@configclass
|
||||
class ObservationsCfg:
|
||||
"""Observation specifications for the MDP."""
|
||||
|
||||
@configclass
|
||||
class PolicyCfg(ObsGroup):
|
||||
"""Observations for policy group."""
|
||||
|
||||
# observation terms (order preserved)
|
||||
base_lin_vel = ObsTerm(func=mdp.base_lin_vel, noise=Unoise(n_min=-0.1, n_max=0.1))
|
||||
base_ang_vel = ObsTerm(func=mdp.base_ang_vel, noise=Unoise(n_min=-0.2, n_max=0.2))
|
||||
projected_gravity = ObsTerm(
|
||||
func=mdp.projected_gravity,
|
||||
noise=Unoise(n_min=-0.05, n_max=0.05),
|
||||
)
|
||||
velocity_commands = ObsTerm(func=mdp.generated_commands, params={"command_name": "base_velocity"})
|
||||
joint_pos = ObsTerm(
|
||||
# 指定计算函数，用于获取关节相对位置
|
||||
func=mdp.joint_pos_rel,
|
||||
# 设置噪声参数，使用均匀分布噪声，最小值为-1e-3，最大值为1e-3
|
||||
noise=Unoise(n_min=-1e-3, n_max=1e-3),
|
||||
# 配置观测参数
|
||||
params={
|
||||
# 指定观测的实体为机器人，并配置关节名称和顺序
|
||||
"asset_cfg": SceneEntityCfg(
|
||||
"robot", # 实体名称为"robot"
|
||||
joint_names=JOINT_NAMES, # 指定要观测的关节名称列表
|
||||
preserve_order=True, # 保持关节顺序不变
|
||||
)
|
||||
},
|
||||
# 设置历史记录长度为5，即保留最近5个时间步的观测数据
|
||||
history_length=5,
|
||||
)
|
||||
joint_vel = ObsTerm(
|
||||
func=mdp.joint_vel,
|
||||
noise=Unoise(n_min=-0.04, n_max=0.04),
|
||||
scale=0.05,
|
||||
params={
|
||||
"asset_cfg": SceneEntityCfg(
|
||||
"robot",
|
||||
joint_names=JOINT_NAMES,
|
||||
preserve_order=True,
|
||||
)
|
||||
},
|
||||
history_length=5,
|
||||
)
|
||||
actions = ObsTerm(func=mdp.last_action)
|
||||
velocity_commands = ObsTerm(
|
||||
func=mdp.generated_commands, # 指定调用的函数，即MDP中的generated_commands方法
|
||||
params={"command_name": "base_velocity"}, # 传递给函数的参数，指定命令名称为"base_velocity"
|
||||
scale=5.0, # 缩放因子，用于调整输出值的大小
|
||||
)
|
||||
'''height_scan = ObsTerm(
|
||||
func=mdp.height_scan,
|
||||
params={"sensor_cfg": SceneEntityCfg("height_scanner")},
|
||||
noise=Unoise(n_min=-0.1, n_max=0.1),
|
||||
clip=(-1.0, 1.0),
|
||||
)'''
|
||||
|
||||
def __post_init__(self):
|
||||
self.enable_corruption = True
|
||||
self.concatenate_terms = True
|
||||
|
||||
# observation groups
|
||||
policy: PolicyCfg = PolicyCfg()
|
||||
|
||||
|
||||
@configclass
|
||||
class EventsCfg:
|
||||
"""Configuration for events."""
|
||||
|
||||
# startup
|
||||
# 创建一个物理材质事件项
|
||||
physics_material = EventTerm(
|
||||
# 指定函数为随机化刚体材质的函数
|
||||
func=mdp.randomize_rigid_body_material,
|
||||
# 设置事件模式为启动时执行
|
||||
mode="startup",
|
||||
# 设置事件参数
|
||||
params={
|
||||
# 配置场景实体，指定为机器人，并匹配所有身体部位
|
||||
"asset_cfg": SceneEntityCfg("robot", body_names=".*"),
|
||||
# 设置静态摩擦力的范围为固定值0.8
|
||||
"static_friction_range": (0.8, 0.8),
|
||||
# 设置动态摩擦力的范围为固定值0.6
|
||||
"dynamic_friction_range": (0.6, 0.6),
|
||||
# 设置恢复系数的范围为固定值0.0（完全非弹性碰撞）
|
||||
"restitution_range": (0.0, 0.0),
|
||||
# 设置材质分桶数量为64
|
||||
"num_buckets": 64,
|
||||
},
|
||||
)
|
||||
|
||||
add_base_mass = EventTerm(
|
||||
func=mdp.randomize_rigid_body_mass,
|
||||
mode="startup",
|
||||
params={
|
||||
"asset_cfg": SceneEntityCfg("robot", body_names="head_link"),
|
||||
# Multiplicative ±25% log-uniform. Scale-invariant across robot sizes
|
||||
# (no per-robot kg overrides needed) with geometric mean 1.0 and
|
||||
# symmetric inverse perturbation (acceleration symmetric around nominal).
|
||||
"mass_distribution_params": (1 / 1.25, 1.25),
|
||||
"operation": "scale",
|
||||
"distribution": "log_uniform",
|
||||
},
|
||||
)
|
||||
|
||||
# 预设基座质心随机化配置
|
||||
base_com = preset( # 使用preset函数创建预设配置
|
||||
default=EventTerm( # 默认事件项配置
|
||||
func=mdp.randomize_rigid_body_com, # 执行的函数：随机化刚体质心
|
||||
mode="startup", # 事件模式：启动时执行
|
||||
params={ # 函数参数配置
|
||||
"asset_cfg": SceneEntityCfg("robot", body_names="head_link"), # 场景实体配置：机器人基座
|
||||
"com_range": {"x": (-0.05, 0.05), "y": (-0.05, 0.05), "z": (-0.01, 0.01)},
|
||||
},
|
||||
),
|
||||
newton_mjwarp=None,
|
||||
)
|
||||
|
||||
# reset
|
||||
# 创建一个外部力矩事件项，用于在重置时对机器人基座施加外部力和力矩
|
||||
base_external_force_torque = EventTerm(
|
||||
# 指定事件处理函数为mdp.apply_external_force_torque
|
||||
func=mdp.apply_external_force_torque,
|
||||
# 设置事件模式为"reset"，表示在环境重置时触发
|
||||
mode="reset",
|
||||
# 设置事件参数
|
||||
params={
|
||||
# 指定目标实体为机器人，并指定施加力的部位为基座
|
||||
"asset_cfg": SceneEntityCfg("robot", body_names="head_link"),
|
||||
# 设置力的范围为(0.0, 0.0)，表示不施加任何力
|
||||
"force_range": (0.0, 0.0),
|
||||
# 设置力矩的范围为(-0.0, 0.0)，表示不施加任何力矩
|
||||
"torque_range": (-0.0, 0.0),
|
||||
},
|
||||
)
|
||||
|
||||
reset_base = EventTerm(
|
||||
func=mdp.reset_root_state_uniform,
|
||||
mode="reset",
|
||||
params={
|
||||
"pose_range": {"x": (-0.5, 0.5), "y": (-0.5, 0.5), "yaw": (-3.14, 3.14)},
|
||||
"velocity_range": {
|
||||
"x": (-0.5, 0.5),
|
||||
"y": (-0.5, 0.5),
|
||||
"z": (-0.5, 0.5),
|
||||
"roll": (-0.5, 0.5),
|
||||
"pitch": (-0.5, 0.5),
|
||||
"yaw": (-0.5, 0.5),
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
# 定义一个重置机器人关节的事件项
|
||||
reset_robot_joints = EventTerm(
|
||||
# 指定事件处理函数为mdp.reset_joints_by_scale
|
||||
func=mdp.reset_joints_by_scale,
|
||||
# 设置事件模式为"reset"
|
||||
mode="reset",
|
||||
# 设置事件参数
|
||||
params={
|
||||
# 设置位置范围为(0.5, 1.5)
|
||||
"position_range": (0.5, 1.5),
|
||||
# 设置速度范围为(0.0, 0.0)
|
||||
"velocity_range": (0.0, 0.0),
|
||||
},
|
||||
)
|
||||
|
||||
# interval
|
||||
# 创建一个名为push_robot的EventTerm对象，用于执行机器人推动操作
|
||||
push_robot = EventTerm(
|
||||
func=mdp.push_by_setting_velocity, # 指定执行函数为mdp中的push_by_setting_velocity
|
||||
mode="interval", # 设置执行模式为间隔模式
|
||||
interval_range_s=(10.0, 15.0), # 设置执行间隔时间范围为10.0到15.0秒
|
||||
params={"velocity_range": {"x": (-0.5, 0.5), "y": (-0.5, 0.5)}}, # 设置推动速度范围，x和y方向的速度范围均为-0.5到0.5
|
||||
)
|
||||
|
||||
|
||||
@configclass
|
||||
class RewardsCfg:
|
||||
"""Reward terms for the MDP."""
|
||||
|
||||
# -- task
|
||||
track_lin_vel_xy_exp = RewTerm(
|
||||
func=mdp.track_lin_vel_xy_exp, weight=1.0, params={"command_name": "base_velocity", "std": math.sqrt(0.25)}
|
||||
)
|
||||
track_ang_vel_z_exp = RewTerm(
|
||||
func=mdp.track_ang_vel_z_exp, weight=0.5, params={"command_name": "base_velocity", "std": math.sqrt(0.25)}
|
||||
)
|
||||
# -- penalties
|
||||
lin_vel_z_l2 = RewTerm(func=mdp.lin_vel_z_l2, weight=-2.0)
|
||||
ang_vel_xy_l2 = RewTerm(func=mdp.ang_vel_xy_l2, weight=-0.05)
|
||||
dof_torques_l2 = RewTerm(func=mdp.joint_torques_l2, weight=-1.0e-5)
|
||||
dof_acc_l2 = RewTerm(func=mdp.joint_acc_l2, weight=-2.5e-7)
|
||||
action_rate_l2 = RewTerm(func=mdp.action_rate_l2, weight=-0.01)
|
||||
feet_air_time = RewTerm(
|
||||
func=mdp.feet_air_time,
|
||||
weight=0.125,
|
||||
params={
|
||||
"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["lf3_link", "rf3_link"]),
|
||||
"command_name": "base_velocity",
|
||||
"threshold": 0.5,
|
||||
},
|
||||
)
|
||||
# 定义一个不期望接触的惩罚项，用于优化机器人运动
|
||||
# 使用RewTerm类创建，其权重为负值，表示对不期望接触的行为进行惩罚
|
||||
undesired_contacts = RewTerm(
|
||||
func=mdp.undesired_contacts, # 指定使用的函数mdp.undesired_contacts，用于计算不期望接触的惩罚
|
||||
weight=-1.0, # 设置权重为-1.0，表示不期望接触的行为会带来负奖励
|
||||
params={"sensor_cfg": SceneEntityCfg("contact_forces", body_names=["head_link", "lf0_link", "rf0_link"]), "threshold": 1.0},
|
||||
)
|
||||
# -- optional penalties
|
||||
flat_orientation_l2 = RewTerm(func=mdp.flat_orientation_l2, weight=0.0)
|
||||
dof_pos_limits = RewTerm(func=mdp.joint_pos_limits, weight=0.0)
|
||||
|
||||
|
||||
@configclass
|
||||
class TerminationsCfg:
|
||||
"""Termination terms for the MDP."""
|
||||
|
||||
time_out = DoneTerm(func=mdp.time_out, time_out=True)
|
||||
base_contact = DoneTerm(
|
||||
func=mdp.illegal_contact,
|
||||
params={"sensor_cfg": SceneEntityCfg("contact_forces",
|
||||
body_names=[
|
||||
"head_link",
|
||||
"lf0_link", "lf1_link", "lf2_link",
|
||||
"rf0_link", "rf1_link", "rf2_link",
|
||||
]), "threshold": 1.0},
|
||||
)
|
||||
|
||||
|
||||
@configclass
|
||||
class CurriculumCfg:
|
||||
"""Curriculum terms for the MDP."""
|
||||
|
||||
# The scene uses a flat plane, so there is no terrain generator to update.
|
||||
terrain_levels = None
|
||||
|
||||
|
||||
##
|
||||
# Environment configuration base
|
||||
##
|
||||
|
||||
|
||||
@configclass
|
||||
class LocomotionVelocityRoughEnvCfg(ManagerBasedRLEnvCfg):
|
||||
"""Configuration for the locomotion velocity-tracking environment."""
|
||||
|
||||
# Simulation settings — shared physics preset (PhysX + MJWarp) for all rough-terrain envs
|
||||
sim: SimulationCfg = SimulationCfg(physics=RoughPhysicsCfg())
|
||||
# Scene settings
|
||||
scene: MySceneCfg = MySceneCfg(num_envs=4096, env_spacing=0.5)
|
||||
# Basic settings
|
||||
observations: ObservationsCfg = ObservationsCfg()
|
||||
actions: ActionsCfg = ActionsCfg()
|
||||
commands: CommandsCfg = CommandsCfg()
|
||||
# MDP settings
|
||||
rewards: RewardsCfg = RewardsCfg()
|
||||
terminations: TerminationsCfg = TerminationsCfg()
|
||||
events: EventsCfg = EventsCfg()
|
||||
curriculum: CurriculumCfg = CurriculumCfg()
|
||||
|
||||
def __post_init__(self):
|
||||
"""Post initialization."""
|
||||
# general settings
|
||||
self.decimation = 4
|
||||
self.episode_length_s = 20.0
|
||||
# simulation settings
|
||||
self.sim.dt = 0.005
|
||||
self.sim.render_interval = self.decimation
|
||||
self.sim.physics_material = self.scene.terrain.physics_material
|
||||
# update sensor update periods
|
||||
# we tick all the sensors based on the smallest update period (physics update period)
|
||||
if self.scene.height_scanner is not None:
|
||||
self.scene.height_scanner.update_period = self.decimation * self.sim.dt
|
||||
if self.scene.contact_forces is not None:
|
||||
self.scene.contact_forces.update_period = self.sim.dt
|
||||
|
||||
# check if terrain levels curriculum is enabled - if so, enable curriculum for terrain generator
|
||||
# this generates terrains with increasing difficulty and is useful for training
|
||||
if getattr(self.curriculum, "terrain_levels", None) is not None:
|
||||
if self.scene.terrain.terrain_generator is not None:
|
||||
self.scene.terrain.terrain_generator.curriculum = True
|
||||
else:
|
||||
if self.scene.terrain.terrain_generator is not None:
|
||||
self.scene.terrain.terrain_generator.curriculum = False
|
||||
Loading…
Reference in New Issue