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FANUC CRX-5iA — GR00T evaluation run 20260827_120840

2 closed-loop episodes of a GR00T N1.7 checkpoint on a real FANUC CRX-5iA, recorded 20260827_120840.

What is here

Per episode:

  • episode_NNN_<port>.mp4 — one video per camera at 15 fps. The yellow band marks the 16:9 crop actually sent to the policy; everything outside it was discarded before the frame went on the wire.
  • episode_NNN_steps.jsonl — one record per control step: observation state, the raw action the policy returned, what the executor commanded after unit conversion and clamping, resulting TCP, and timings.
  • summary.json — the full run record including every threshold, so the numbers stay readable after those constants move.
  • run.log — the operator-visible log.

Results

ep outcome steps wall s result class cos_align path mm out-of-range
0 budget 400 483.16 failure GRASP_DROP -0.46 798 144
1 budget 400 483.46 failure GRASP_MISPLACE -0.43 1192 400

out-of-range counts control steps whose observation state fell outside the checkpoint's corpus bands (state_limits in summary.json), out of 400 steps per episode. Run total: 544 of 800.

Conditions

Checkpoint /cache/adapters/n17_droid_mem_llm4_085000/pretrained_model
Task string pick up the dice and place it on the white block
Cameras sent cam0, cam1, cam2
Frame geometry source → 1.7777777777777777 aspect by crop
Delivered shapes {"cam0": [480, 640, 3], "cam1": [480, 640, 3], "cam2": [480, 640, 3]}
JPEG quality 80 (the training corpus is lossless renders)
Start orientation plumb, tilt gate 5.0 deg
Step budget 400 rows, 600.0 s wall clock
State gate observe
Control period ~1.2 s per action row (training dataset is 15 fps)

Success criterion

success_at_end: the dice must be on the block that was bare at episode start, within on_block_mm. Every threshold is stamped in summary.json.

Provenance

Recorded by fanuc_control.inference.evaluate. The oracle (dice and bare-block positions) is measured before each episode and deliberately NOT executed; it exists only to score against.

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