Comments (2)
Yes that part of the code is not released. What we did is to use the physical ALOHA leader arms to teleoperate the simulated ALOHA follower arms. The operator watches the rendering of the mujoco env on a monitor.
Check out this function to get a rough sense of it. Note it will not run without ALOHA hardware. https://github.com/tonyzhaozh/act/blob/main/sim_env.py#L246
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Yes that part of the code is not released. What we did is to use the physical ALOHA leader arms to teleoperate the simulated ALOHA follower arms. The operator watches the rendering of the mujoco env on a monitor.
Check out this function to get a rough sense of it. Note it will not run without ALOHA hardware. https://github.com/tonyzhaozh/act/blob/main/sim_env.py#L246
What is the format of source of data(https://github.com/tonyzhaozh/act/blob/main/sim_env.py#L253,https://github.com/tonyzhaozh/act/blob/main/sim_env.py#L255 ),We have a robotic arm in our lab that also has cameras, and based on your experimental process, we thought we could link the Mujoco emulator to our robotic arm and use the data from our lab's robotic arm to drive the Mujoco emulator to acquire the corresponding data.
Can you post the format of master_bot_left
and master_bot_right
that you ran out and I'll get the corresponding data on my robotic arm
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Related Issues (20)
- DETR VEA uses output of first layer of transformer decoder? HOT 3
- Missing packages to run?
- From where to get checkpoints please?
- Simulation issues
- ModuleNotFoundError: No module named 'util' HOT 1
- ModuleNotFoundError: No module named 'robomimic.algo.diffusion_policy' HOT 13
- From joint postion to end-effector position? HOT 1
- Extremely poor validation results on self-trained checkpoints HOT 9
- Asking for best_ckpt
- ALOHA2 simulation support
- Why use leader robots joint positions as Supervision rather than the follow's HOT 2
- Why are encoder heads so important when training?
- discrepancy in results
- Potential bug in the transformer.py and detr_vae.py? HOT 1
- CVAE and DETR
- issue of scripted_policy
- Policy roll-out in real-world results in the same action prediction at every timestep HOT 4
- AttributeError: 'RealEnv' object has no attribute '_physics' HOT 1
- which coordinate system are the actions involved in training? HOT 1
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