Patch Policy — real robot, two views
This private model repository contains a LeRobot-compatible export of the
latest completed two-view Patch Policy checkpoint. It uses
observation.images.front and observation.images.ee, with a two-frame
observation context and five-action prediction horizon.
Training data: 16 episodes, 10,342 frames, 30 FPS, six joint-position actions
and the so_follower robot schema. The intended training run is 50,000
optimizer steps; the latest exported snapshot in this repository is step
15,000. Raw training checkpoints are preserved under backups/.
LeRobot rollout
The root files are in LeRobot's pretrained-policy layout:
config.json, model.safetensors, policy_preprocessor.json, and
policy_postprocessor.json.
The custom policy must be installed once in the LeRobot environment so the
standard lerobot-rollout plugin discovery can register patchpol:
uv pip install -e /path/to/this/repository/lerobot_plugin
lerobot-rollout --policy.path=atharva-pantheon/patchpol-so-follower-multiview \
--robot.type=so100_follower
Supply the robot's normal port/calibration/camera arguments. The robot must provide both camera feature keys with the names above. DINOv2 ViT-S/14 is a frozen runtime dependency and is loaded from the local Torch Hub cache (the first run may download it).
The action postprocessor restores the recorded six-dimensional action scale using the dataset statistics included in the processor state files.
- Downloads last month
- 16