102 lines
3.2 KiB
Python
102 lines
3.2 KiB
Python
# 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.
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#
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# SPDX-License-Identifier: BSD-3-Clause
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"""Script to an environment with random action agent."""
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"""Launch Isaac Sim Simulator first."""
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import argparse
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import os
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from isaaclab.app import AppLauncher
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# add argparse arguments
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parser = argparse.ArgumentParser(description="Random agent for Isaac Lab environments.")
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parser.add_argument("--task", type=str, default=None, help="Name of the task.")
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parser.add_argument("--output_dir", type=str, default=None, help="Path to the output directory.")
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# append AppLauncher cli args
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AppLauncher.add_app_launcher_args(parser)
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# parse the arguments
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args_cli = parser.parse_args()
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args_cli.headless = True
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# launch omniverse app
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app_launcher = AppLauncher(args_cli)
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simulation_app = app_launcher.app
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"""Rest everything follows."""
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import gymnasium as gym
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import torch
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import isaaclab_tasks # noqa: F401
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from isaaclab_tasks.utils import parse_env_cfg
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# PLACEHOLDER: Extension template (do not remove this comment)
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def main():
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"""Random actions agent with Isaac Lab environment."""
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# create environment configuration
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env_cfg = parse_env_cfg(args_cli.task, device=args_cli.device, num_envs=1, use_fabric=True)
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# create environment
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env = gym.make(args_cli.task, cfg=env_cfg)
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# print info (this is vectorized environment)
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print(f"[INFO]: Gym observation space: {env.observation_space}")
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print(f"[INFO]: Gym action space: {env.action_space}")
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# reset environment
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env.reset()
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outs = env.unwrapped.get_IO_descriptors
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out_observations = outs["observations"]
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out_actions = outs["actions"]
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out_articulations = outs["articulations"]
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out_scene = outs["scene"]
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# Make a yaml file with the output
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import yaml
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name = args_cli.task.lower().replace("-", "_")
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name = name.replace(" ", "_")
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if not os.path.exists(args_cli.output_dir):
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os.makedirs(args_cli.output_dir)
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with open(os.path.join(args_cli.output_dir, f"{name}_IO_descriptors.yaml"), "w") as f:
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print(f"[INFO]: Exporting IO descriptors to {os.path.join(args_cli.output_dir, f'{name}_IO_descriptors.yaml')}")
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yaml.safe_dump(outs, f)
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for k in out_actions:
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print(f"--- Action term: {k['name']} ---")
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k.pop("name")
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for k1, v1 in k.items():
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print(f"{k1}: {v1}")
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for obs_group_name, obs_group in out_observations.items():
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print(f"--- Obs group: {obs_group_name} ---")
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for k in obs_group:
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print(f"--- Obs term: {k['name']} ---")
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k.pop("name")
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for k1, v1 in k.items():
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print(f"{k1}: {v1}")
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for articulation_name, articulation_data in out_articulations.items():
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print(f"--- Articulation: {articulation_name} ---")
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for k1, v1 in articulation_data.items():
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print(f"{k1}: {v1}")
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for k1, v1 in out_scene.items():
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print(f"{k1}: {v1}")
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env.step(torch.zeros(env.action_space.shape, device=env.unwrapped.device))
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env.close()
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if __name__ == "__main__":
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# run the main function
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main()
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# close sim app
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simulation_app.close()
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