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@rojas70 rojas70 commented Jun 11, 2025

Commit 422d207 fixes a bug in the way the Mujoco Renderer is instantiated so that there is no crush when calling. test_gym_env_human.py.

Commit 7e23bbd includes a critic_actor_ratio that is missing when agent.high_utd_ratio is called.

Others...

rojas70 and others added 29 commits August 21, 2025 22:26
- Set original image resolution to (960,960,3) for easy viewing.
- Need to resize these images in the SERLObsWrapper such that image specs match those expected by DRQ as well as ensure they are of type uint8.
- resize function added that can work with cv2 or PIL.
- Call to observation returns state and resized images. Lots of checks here.
- Can record demos for any number of episodes.
- Keyboard bindings use the following keys:
moveBindings = {
    'i':(1,0,0,0),
    ',':(-1,0,0,0),
    'j':(0,1,0,0),
    'l':(0,-1,0,0),
    'u':(0,0,0,1),
    'o':(0,0,0,-1),
    'm':(0,0,1,0),
    '.':(0,0,-1,0),
        }

Note that after commanding actions the robot has some momentum that current controller does not cancel well. You will need practice.
- Data gets stored to data customized folders that are checked for existance or created.
…s well using: a,d,w,s,q,e to change azimuth, elevation, and distance.

- code checks first for cam if so, then checks for action. if no cam, then just checks for action.
- correctly updates OXEEnvLogger generated files to be read by TFDS tfds.builder_from_directory in launcher.py
- When running outside debugger still get an exception that I need to work out, but can be used to move forward.
- Changing name of env to sparse reach version.
- In demos branch, fixing jax.tree.leaves.
- Reward is 1 for success cases based on the error norm proximity.
- Slight change to step function.
- Increased max-steps to 200 for this environment.
… using a format similar to the following:

└── franka_reach_drq_demo_script
    ├── session_20250914_210112_num_demos_2
    │   └── PandaReachSparseCube-v0
    │       └── 0.1.0
    │           ├── dataset_info.json
    │           ├── features.json
    │           └── PandaReachSparseCube-v0-train.tfrecord-00000

Succeeded in recording 2,5,10 demos for Panda Reach Sparse with Cube.
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Ultimately what name are we using for the environment. I thought we had agreed on a 'Vision' named environment.

Currently I see: PandaReachSparseCube

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4 participants