google-deepmind / google-deepmind/mujoco_playground
G1 policy deployment questions
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Hi All,
Thanks for open-sourcing this awesome project!
I've been trying to reproduce the G1 locomotion results on real hardware but haven’t had a successful run so far. Meanwhile, I was able to deploy unitree_rsl_gym successfully. Hence, I have a few questions:
1. Your XML model seems slightly different—for example, it has separate Kp, damping, and armature parameters compared to unitree_rsl_gym's model. Did you perform system identification with the real hardware?
2. Do PD gains in MJX have a different meaning compared to Isaac and hardware? Could you provide the hardware PD gains being used?
3. I've been tuning the rewards, but there are probably more factors to consider. Could you share your G1JoyStickFlatTerrain configurations (scales, noises, PPO parameters, etc.) and any insights on deployment?
4. I plan to remove linear velocity or anything requiring state estimation. This worked for unitree_rsl_gym with LSTM policies. Do you think this would work in your case?
I look forward to your response.
Many thanks,
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