README.md

metadata

license: other
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
tags:
  - robotics
  - pi0.5
  - openpi
  - lora
  - tactile
  - xarm
base_model: physical-intelligence/pi05_droid

pi05_xarm_dishwasher_points9_arrow_len0_lora

pi0.5 (openpi) LoRA fine-tune for the xArm dishwasher task ("pull the basket outside of the dishwasher and pick up the mug and put it into the basket"), trained on camera frames with the points9_arrow_len0 tactile overlay: 9 tactile-pad dots per finger at FK-projected positions, force arrows at zero length — the force-information ablation of points9_arrow.

Training

Base	pi05_droid (knowledge-insulated pi0.5, DROID pre-training)
Recipe	LoRA r16/a16 on Gemma-2B backbone + r32/a32 on 300M action expert, attn+ffn
Batch / LR	8 / cosine 1e-4 -> 1e-5, 500 warmup, AdamW, grad-clip 1.0
Data	EdwardoSunny/xarm_dishwasher_points9_arrow_len0 (100 eps, 28096 frames)
Early stop	step 7800 (rolling-1k-window <0.5% rel. improvement, 2 consecutive checks)
Final train loss	0.0287 (baseline no-overlay: 0.029; full points9_arrow: 0.024)

Training-loss comparison across this task's variants (identical hyperparameters/protocol, only the burned-in overlay differs) — see the collection for all four tasks.

Contents

• params/ — merged base+LoRA weights (orbax), self-contained for inference
• assets/local/xarm_dishwasher_points9_arrow_len0/norm_stats.json — state/action normalization
• Optimizer state stripped (inference-ready). Config name: pi05_xarm_dishwasher_points9_arrow_len0_lora

Deployment note

At inference, render the live camera frames with the SAME overlay (SensorDrawer mode points9_arrow, arrow_length_scale=0, thickness 8, dot size 22) or the policy will be out-of-distribution. See tactile-data-collection/scripts/render_arrowlen0.py.