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1、资产导入

• 在isaacgym中，机器人结构文件(.urdf)保存在resources目录下
• 在isaaclab的文件结构里有所不同，isaaclab使用USD格式文件，此时导入新机器人需要将urdf文件转换成USD文件。

1.1 文件准备

首先在宇树官方文档中拿到RL例程，把unitree_rl_gym文件夹放在根目录\home\username\下

1.2 资产导入

需要调用scripts/tools/convert_urdf.py脚本进行转换，其中涉及到一些参数的设置：

参数名	描述	默认值
--merge-joints	布尔标志，设置为True时，合并由固定关节连接的连杆	False
--fix-base	布尔标志，设置为True时，将机器人基座固定在导入位置	False
--joint-stiffness	关节驱动的刚度，刚度值越大，关节越难变形	100.0
--joint-damping	关节驱动的阻尼，用于减少关节的振动和摆动	1.0
--joint-target-type	关节驱动的控制类型，可选值为"position"、“velocity"或"none”	“position”

cd IsaacLab./isaaclab.sh -p scripts/tools/convert_urdf.py \
~/unitree_rl_gym/resources/robots/h1_2/h1_2.urdf \
source/isaaclab_assets/data/Robots/h1_2/h1_2.usd \
--merge-joints --joint-stiffness 0.0 \
--joint-damping 0.0 \
--joint-target-type none

导入到isaacsim中：

这个时候USD文件就生成了。

2、机器人属性配置

对标gym中的config，在IsaacLab中也要写一个对应的config。
在IsaacLab/source/isaaclab_assets/isaaclab_assets/robots/中找到了机器人们的配置文件，其中有一个文件为unitree.py，里面配置了Isaaclab收录的所有宇树机器人，但是H1_2恰好没在其中。

模仿unitree.py中关于H1的配置，再参考H1_2的关节，写一段config插在unitree.py中：
其中有几点需要注意：

• usd_path需要对应自己的usd文件的路径
• H1_2相比于H1而言，关节名称有些许变化（具体是名称后面多了“_joint”，以及ankle等部位多加了关节），正则表达式匹配需要在后面也加个 $\text{.*}$

H1_2_CFG = ArticulationCfg(spawn=sim_utils.UsdFileCfg(usd_path=f"/home/swanchan/IsaacLab/source/isaaclab_assets/data/Robots/h1_2/h1_2.usd",activate_contact_sensors=True,rigid_props=sim_utils.RigidBodyPropertiesCfg(disable_gravity=False,retain_accelerations=False,linear_damping=0.0,angular_damping=0.0,max_linear_velocity=1000.0,max_angular_velocity=1000.0,max_depenetration_velocity=1.0,),articulation_props=sim_utils.ArticulationRootPropertiesCfg(enabled_self_collisions=False, solver_position_iteration_count=4, solver_velocity_iteration_count=4),),init_state=ArticulationCfg.InitialStateCfg(pos=(0.0, 0.0, 1.05),joint_pos={".*_hip_yaw.*": 0.0,".*_hip_roll.*": 0.0,".*_hip_pitch.*": -0.16,  # -9.17 degrees".*_knee.*": 0.36,  # 20.63 degrees".*_ankle_pitch.*": -0.2,  # -11.46 degrees".*_ankle_roll.*": 0.0,"torso.*": 0.0,".*_shoulder_pitch.*": 0.4,  # 22.92 degrees".*_shoulder_roll.*": 0.0,".*_shoulder_yaw.*": 0.0,".*_elbow_pitch.*": 0.3,  # 17.19 degrees},joint_vel={".*": 0.0},),soft_joint_pos_limit_factor=0.9,actuators={"legs": ImplicitActuatorCfg(joint_names_expr=[".*_hip_yaw.*", ".*_hip_roll.*", ".*_hip_pitch.*", ".*_knee.*", "torso.*"],effort_limit=300,velocity_limit=100.0,stiffness={".*_hip_yaw.*": 200.0,".*_hip_roll.*": 200.0,".*_hip_pitch.*": 200.0,".*_knee.*": 300.0,"torso.*": 200.0,},damping={".*_hip_yaw.*": 2.5,".*_hip_roll.*": 2.5,".*_hip_pitch.*": 2.5,".*_knee.*": 4.0,"torso.*": 5.0,},),"feet": ImplicitActuatorCfg(joint_names_expr=[".*_ankle_pitch.*", ".*_ankle_roll.*"],effort_limit=100,velocity_limit=100.0,stiffness={".*_ankle_pitch.*": 40.0,".*_ankle_roll.*": 40.0,},damping={".*_ankle_pitch.*": 2.0,".*_ankle_roll.*": 2.0,},),"arms": ImplicitActuatorCfg(joint_names_expr=[".*_shoulder_pitch.*", ".*_shoulder_roll.*", ".*_shoulder_yaw.*", ".*_elbow_pitch.*"],effort_limit=300,velocity_limit=100.0,stiffness={".*_shoulder_pitch.*": 40.0,".*_shoulder_roll.*": 40.0,".*_shoulder_yaw.*": 40.0,".*_elbow_pitch.*": 40.0,},damping={".*_shoulder_pitch.*": 10.0,".*_shoulder_roll.*": 10.0,".*_shoulder_yaw.*": 10.0,".*_elbow_pitch.*": 10.0,},),},
)
"""Configuration for the Unitree H1_2 Humanoid robot."""H1_2_MINIMAL_CFG = H1_2_CFG.copy()
H1_2_MINIMAL_CFG.spawn.usd_path = f"{ISAACLAB_NUCLEUS_DIR}/Robots/Unitree/H1_2/h1_2_minimal.usd"

3、强化学习任务环境配置

在/IsaacLab/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/中可以看到宇树的机器人训练环境

直接把h1文件夹复制为h1_2，然后对里面的文件进行一定的更改。
具体是把所有h1替换为h1_2，所有H1替换为H1_2，再改一下rough_env_cfg.py里面的关节

__init__.py

# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clauseimport gymnasium as gymfrom . import agents##
# Register Gym environments.
##gym.register(id="Isaac-Velocity-Rough-H1_2-v0",entry_point="isaaclab.envs:ManagerBasedRLEnv",disable_env_checker=True,kwargs={"env_cfg_entry_point": f"{__name__}.rough_env_cfg:H1_2RoughEnvCfg","rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1_2RoughPPORunnerCfg","skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml",},
)gym.register(id="Isaac-Velocity-Rough-H1_2-Play-v0",entry_point="isaaclab.envs:ManagerBasedRLEnv",disable_env_checker=True,kwargs={"env_cfg_entry_point": f"{__name__}.rough_env_cfg:H1_2RoughEnvCfg_PLAY","rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1_2RoughPPORunnerCfg","skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml",},
)gym.register(id="Isaac-Velocity-Flat-H1_2-v0",entry_point="isaaclab.envs:ManagerBasedRLEnv",disable_env_checker=True,kwargs={"env_cfg_entry_point": f"{__name__}.flat_env_cfg:H1_2FlatEnvCfg","rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1_2FlatPPORunnerCfg","skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml",},
)gym.register(id="Isaac-Velocity-Flat-H1_2-Play-v0",entry_point="isaaclab.envs:ManagerBasedRLEnv",disable_env_checker=True,kwargs={"env_cfg_entry_point": f"{__name__}.flat_env_cfg:H1_2FlatEnvCfg_PLAY","rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1_2FlatPPORunnerCfg","skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml",},
)

flat_env_cfg.py

# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clausefrom isaaclab.utils import configclassfrom .rough_env_cfg import H1_2RoughEnvCfg@configclass
class H1_2FlatEnvCfg(H1_2RoughEnvCfg):def __post_init__(self):# post init of parentsuper().__post_init__()# change terrain to flatself.scene.terrain.terrain_type = "plane"self.scene.terrain.terrain_generator = None# no height scanself.scene.height_scanner = Noneself.observations.policy.height_scan = None# no terrain curriculumself.curriculum.terrain_levels = Noneself.rewards.feet_air_time.weight = 1.0self.rewards.feet_air_time.params["threshold"] = 0.6class H1_2FlatEnvCfg_PLAY(H1_2FlatEnvCfg):def __post_init__(self) -> None:# post init of parentsuper().__post_init__()# make a smaller scene for playself.scene.num_envs = 50self.scene.env_spacing = 2.5# disable randomization for playself.observations.policy.enable_corruption = False# remove random pushingself.events.base_external_force_torque = Noneself.events.push_robot = None

rough_env_cfg.py

# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clausefrom isaaclab.managers import RewardTermCfg as RewTerm
from isaaclab.managers import SceneEntityCfg
from isaaclab.utils import configclassimport isaaclab_tasks.manager_based.locomotion.velocity.mdp as mdp
from isaaclab_tasks.manager_based.locomotion.velocity.velocity_env_cfg import LocomotionVelocityRoughEnvCfg, RewardsCfg##
# Pre-defined configs
##
from isaaclab_assets import H1_2_CFG@configclass
class H1_2Rewards(RewardsCfg):"""Reward terms for the MDP."""termination_penalty = RewTerm(func=mdp.is_terminated, weight=-200.0)lin_vel_z_l2 = Nonetrack_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},)track_ang_vel_z_exp = RewTerm(func=mdp.track_ang_vel_z_world_exp, weight=1.0, params={"command_name": "base_velocity", "std": 0.5})feet_air_time = RewTerm(func=mdp.feet_air_time_positive_biped,weight=0.25,params={"command_name": "base_velocity","sensor_cfg": SceneEntityCfg("contact_forces", body_names=".*ankle.*"),"threshold": 0.4,},)feet_slide = RewTerm(func=mdp.feet_slide,weight=-0.25,params={"sensor_cfg": SceneEntityCfg("contact_forces", body_names=".*ankle.*"),"asset_cfg": SceneEntityCfg("robot", body_names=".*ankle.*"),},)# Penalize ankle joint limitsdof_pos_limits = RewTerm(func=mdp.joint_pos_limits, weight=-1.0, params={"asset_cfg": SceneEntityCfg("robot", joint_names=".*_ankle.*")})# Penalize deviation from default of the joints that are not essential for locomotionjoint_deviation_hip = RewTerm(func=mdp.joint_deviation_l1,weight=-0.2,params={"asset_cfg": SceneEntityCfg("robot", joint_names=[".*_hip_yaw.*", ".*_hip_roll.*"])},)joint_deviation_arms = RewTerm(func=mdp.joint_deviation_l1,weight=-0.2,params={"asset_cfg": SceneEntityCfg("robot", joint_names=[".*_shoulder_.*", ".*_elbow.*"])},)joint_deviation_torso = RewTerm(func=mdp.joint_deviation_l1, weight=-0.1, params={"asset_cfg": SceneEntityCfg("robot", joint_names="torso.*")})@configclass
class H1_2RoughEnvCfg(LocomotionVelocityRoughEnvCfg):rewards: H1_2Rewards = H1_2Rewards()def __post_init__(self):# post init of parentsuper().__post_init__()# Sceneself.scene.robot = H1_2_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot") # type: ignoreif self.scene.height_scanner:self.scene.height_scanner.prim_path = "{ENV_REGEX_NS}/Robot/torso_link"# Randomizationself.events.push_robot = Noneself.events.add_base_mass = Noneself.events.reset_robot_joints.params["position_range"] = (1.0, 1.0)self.events.base_external_force_torque.params["asset_cfg"].body_names = [".*torso_link"]self.events.reset_base.params = {"pose_range": {"x": (-0.5, 0.5), "y": (-0.5, 0.5), "yaw": (-3.14, 3.14)},"velocity_range": {"x": (0.0, 0.0),"y": (0.0, 0.0),"z": (0.0, 0.0),"roll": (0.0, 0.0),"pitch": (0.0, 0.0),"yaw": (0.0, 0.0),},}# Terminationsself.terminations.base_contact.params["sensor_cfg"].body_names = [".*torso_link"]# Rewardsself.rewards.undesired_contacts = Noneself.rewards.flat_orientation_l2.weight = -1.0self.rewards.dof_torques_l2.weight = 0.0self.rewards.action_rate_l2.weight = -0.005self.rewards.dof_acc_l2.weight = -1.25e-7# Commandsself.commands.base_velocity.ranges.lin_vel_x = (0.0, 1.0)self.commands.base_velocity.ranges.lin_vel_y = (0.0, 0.0)self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0)# terminationsself.terminations.base_contact.params["sensor_cfg"].body_names = ".*torso_link"@configclass
class H1_2RoughEnvCfg_PLAY(H1_2RoughEnvCfg):def __post_init__(self):# post init of parentsuper().__post_init__()# make a smaller scene for playself.scene.num_envs = 50self.scene.env_spacing = 2.5self.episode_length_s = 40.0# spawn the robot randomly in the grid (instead of their terrain levels)self.scene.terrain.max_init_terrain_level = None# reduce the number of terrains to save memoryif self.scene.terrain.terrain_generator is not None:self.scene.terrain.terrain_generator.num_rows = 5self.scene.terrain.terrain_generator.num_cols = 5self.scene.terrain.terrain_generator.curriculum = Falseself.commands.base_velocity.ranges.lin_vel_x = (1.0, 1.0)self.commands.base_velocity.ranges.lin_vel_y = (0.0, 0.0)self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0)self.commands.base_velocity.ranges.heading = (0.0, 0.0)# disable randomization for playself.observations.policy.enable_corruption = False# remove random pushingself.events.base_external_force_torque = Noneself.events.push_robot = None

rsl_rl_ppo_cfg.py

# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clausefrom isaaclab.utils import configclassfrom isaaclab_rl.rsl_rl import RslRlOnPolicyRunnerCfg, RslRlPpoActorCriticCfg, RslRlPpoAlgorithmCfg@configclass
class H1_2RoughPPORunnerCfg(RslRlOnPolicyRunnerCfg):num_steps_per_env = 24max_iterations = 3000save_interval = 50experiment_name = "H1_2_rough"empirical_normalization = Falsepolicy = RslRlPpoActorCriticCfg(init_noise_std=1.0,actor_hidden_dims=[512, 256, 128],critic_hidden_dims=[512, 256, 128],activation="elu",)algorithm = RslRlPpoAlgorithmCfg(value_loss_coef=1.0,use_clipped_value_loss=True,clip_param=0.2,entropy_coef=0.01,num_learning_epochs=5,num_mini_batches=4,learning_rate=1.0e-3,schedule="adaptive",gamma=0.99,lam=0.95,desired_kl=0.01,max_grad_norm=1.0,)@configclass
class H1_2FlatPPORunnerCfg(H1_2RoughPPORunnerCfg):def __post_init__(self):super().__post_init__()self.max_iterations = 1000self.experiment_name = "H1_2_flat"self.policy.actor_hidden_dims = [128, 128, 128]self.policy.critic_hidden_dims = [128, 128, 128]

最后，在IsaacLab目录下执行训练脚本，就可以开始训练啦

./isaaclab.sh -p scripts/reinforcement_learning/rsl_rl/train.py --task Isaac-Velocity-Rough-H1_2-v0 --headless