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The Official Code for Cross-Modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning (NeurIPS'21))

Home Page: https://proceedings.neurips.cc/paper/2021/hash/68264bdb65b97eeae6788aa3348e553c-Abstract.html

License: MIT License

Python 86.76% Jupyter Notebook 13.24%
domain-adaptation reinforcement-learning sim2real

codas's People

Contributors

jiangsy avatar typoverflow avatar ucaschief avatar x35f avatar xionghuichen avatar

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Forkers

lamda-rl yuni1314 typoverflow

codas's Issues

[Bug]: no reference to InvertedDoublePendulmEnvv4

It seems to be an error that InvertedDoublePendulmEnv-v4 is used instead of -v5, for I cannot find its definition anywhere in this code base.

Related snippets include:

CODAS/codas/wrapper/env_wrapper.py

Lines 144 to 153 in 4e8c375

elif isinstance(self.env.env.env, InvertedDoublePendulumEnvv4):
qpos1 = ob[0:1]
qpos2 = np.arcsin(ob[1:raw_env.model.nq])
qpos = np.concatenate([qpos1, qpos2])
qvel = ob[raw_env.model.nq + raw_env.model.nq - 1:raw_env.model.nq + raw_env.model.nq - 1 + raw_env.model.nv]
elif isinstance(self.env.env.env, InvertedDoublePendulumEnvv5):
qpos1 = ob[0:1]
qpos2 = np.arcsin(ob[1:raw_env.model.nq])
qpos = np.concatenate([qpos1, qpos2])
qvel = ob[raw_env.model.nq + raw_env.model.nq - 1:raw_env.model.nq + raw_env.model.nq - 1 + raw_env.model.nv]

  • maybe comment L144-L148?

CODAS/codas/__init__.py

Lines 22 to 26 in 4e8c375

register(
id='InvertedDouble-v4',
max_episode_steps=1000,
entry_point='codas.reset_able_mj_env.inverted_double_pendulum_v4:InvertedDoublePendulumEnv',
)

  • id and the entry point should be -v5?

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