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np.ndarray.shape = (640, 480, 3).np.ndarray.shape = 6 where each element represents the joint control.1SO101Env(
2 xml_pth=Path("assets/SO-ARM100/Simulation/SO101/scene_with_cube.xml"),
3 obs_w=640,
4 obs_h=480)
5env = gym.make(
6 "base-sO101-env-v0",
7)
8try:
9 obs, _ = env.reset()
10 for i in range(10):
11 action = env.action_space.sample()
12 obs, reward, terminated, truncated, info = env.step(action)
13 if terminated or truncated:
14 break
15finally:
16 env.close()
171@software{Knight_Standard_Open_SO-100,
2 author = {Knight, Rob and Kooijmans, Pepijn and Cadene, Remi and Alibert, Simon and Aractingi, Michel and Aubakirova, Dana and Zouitine, Adil and Martino, Russi and Palma, Steven and Pascal, Caroline and Wolf, Thomas},
3 title = {{Standard Open SO-100 \& SO-101 Arms}},
4 url = {https://github.com/TheRobotStudio/SO-ARM100}
5}1@inproceedings{todorov2012mujoco,
2 title={MuJoCo: A physics engine for model-based control},
3 author={Todorov, Emanuel and Erez, Tom and Tassa, Yuval},
4 booktitle={2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
5 pages={5026--5033},
6 year={2012},
7 organization={IEEE},
8 doi={10.1109/IROS.2012.6386109}
9}