Abstraction_experiment arm models

Weights and planner data used by the g1_arm_abs package of Abstraction_experiment (Unitree G1 vision-guided grasping, elevator-button press and berry picking, ROS Noetic).

Directory Contents Used by
grasp_bottle/{left,right}/ MLP inverse-kinematics model (best_model.pth) + input scaler (x_scaler.pkl) per arm grasp_bottle, *_grasp_from_point services
elevator_button/{left,right}/ MLP IK model + scaler + config.json per arm press_elevator_button
grasp_berry/{left,right}/ MLP IK model + scaler per arm pick_berry
abstraction_map/ Voxel A* planner data: per-arm reachability bitmaps (voxel_config_bitmap_{left,right}.uint8, ~14 GB each), feasibility masks, sparse voxel maps, phase-2 metadata and logs Obstacle-aware A* on every planned motion

The two voxel_config_bitmap_*.uint8 files total about 28 GB; make sure you have the disk space before fetching.

Fetch

The project pins this repo's commit and every file's sha256 in g1_arm_abs/config/model_weights.yaml; rosrun g1_arm_abs fetch_weights.py downloads and verifies them into g1_arm_abs/models/ preserving this directory layout. Manual download:

hf download Mattewkang/Abstraction_experiment-arm-models --local-dir g1_arm_abs/models
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