The demo of get up

rl_game/get_up/train.py

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+import sys
+import os
+import argparse
+
+# 确保能找到项目根目录下的模块
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+from isaaclab.app import AppLauncher
+
+# 1. 配置启动参数
+parser = argparse.ArgumentParser(description="Train T1 robot to Get-Up with RL-Games.")
+parser.add_argument("--num_envs", type=int, default=16384, help="起身任务建议并行 4096 即可")
+parser.add_argument("--task", type=str, default="Isaac-T1-GetUp-v0", help="任务 ID")
+parser.add_argument("--seed", type=int, default=42, help="随机种子")
+AppLauncher.add_app_launcher_args(parser)
+args_cli = parser.parse_args()
+
+# 2. 启动仿真器（必须在导入其他 isaaclab 模块前）
+app_launcher = AppLauncher(args_cli)
+simulation_app = app_launcher.app
+
+import torch
+import gymnasium as gym
+import yaml
+from isaaclab_rl.rl_games import RlGamesVecEnvWrapper
+from rl_games.torch_runner import Runner
+from rl_games.common import env_configurations, vecenv
+
+# 导入你刚刚修改好的配置类
+# 假设你的文件名是 t1_getup_cfg.py，类名是 T1EnvCfg
+from config.t1_env_cfg import T1EnvCfg
+
+# 3. 注册环境
+gym.register(
+    id="Isaac-T1-GetUp-v0",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv",
+    kwargs={
+        "cfg": T1EnvCfg(),  # 这里会加载你设置的随机旋转、时间惩罚等
+    },
+)
+
+
+def main():
+    # 4. 创建环境，显式传入命令行指定的 num_envs
+    env = gym.make("Isaac-T1-GetUp-v0", num_envs=args_cli.num_envs)
+
+    # 5. 包装环境
+    # 注意：rl_device 必须设置为 args_cli.device (通常是 'cuda:0')
+    wrapped_env = RlGamesVecEnvWrapper(
+        env,
+        rl_device=args_cli.device,
+        clip_obs=5.0,
+        clip_actions=1.0  # 动作裁剪建议设小一点，防止电机输出瞬间爆表
+    )
+
+    # 注册给 rl_games 使用
+    vecenv.register('as_is', lambda config_name, num_actors, **kwargs: wrapped_env)
+
+    env_configurations.register('rlgym', {
+        'vecenv_type': 'as_is',
+        'env_creator': lambda **kwargs: wrapped_env
+    })
+
+    # 6. 加载 PPO 配置文件
+    # 提示：由于是起身任务，建议在 ppo_cfg.yaml 中调大 mini_batch 大数或提高学习率
+    config_path = os.path.join(os.path.dirname(__file__), "config", "ppo_cfg.yaml")
+    with open(config_path, "r") as f:
+        rl_config = yaml.safe_load(f)
+
+    # 设置日志和实验名称
+    rl_game_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "."))
+    log_dir = os.path.join(rl_game_dir, "logs")
+    rl_config['params']['config']['train_dir'] = log_dir
+    rl_config['params']['config']['name'] = "T1_GetUp_Experiment"
+
+    # 7. 运行训练
+    runner = Runner()
+    runner.load(rl_config)
+
+    print(f"[INFO]: 开始训练任务 {args_cli.task}，环境数量: {args_cli.num_envs}")
+
+    runner.run({
+        "train": True,
+        "play": False,
+        "vec_env": wrapped_env
+    })
+
+    simulation_app.close()
+
+
+if __name__ == "__main__":
+    main()