Datasets:
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action list | observation.state list | timestamp float32 0 59.9 ⌀ | frame_index int64 0 1.8k ⌀ | episode_index int64 0 37 ⌀ | index int64 0 57.8k ⌀ | task_index int64 0 0 ⌀ |
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End of preview. Expand in Data Studio
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rollout_eval_tac_mlp
Rollout evaluation of Jingyi-Z/act-sotac-tac-mlp (ACT + raw tactile frame
token, trained on sotac ep 0-70) on the SO-101 bench, 2026-09-16.
Protocol: bowl fixed at point 1, ball at points 6, 5, 4, 3, 2, 7; five consecutive 60 s episodes per scene, 30 s reset. Stock lerobot 0.6.1 rollout with the so101_paxini robot type; observation.state is 318-dim (6 joints + 312 tactile forces at 30 Hz), so tactile is recorded in every episode. Cameras: top idx 0, wrist idx 2.
Episode map
| Episodes | Scene | Note |
|---|---|---|
| 0-4 | discard | tactile finger order swapped vs training |
| 5-7 | discard | stale calibration, systematic reach offset |
| 8-12 | 1-6 | valid |
| 13-17 | 1-5 | valid |
| 18-22 | 1-4 | valid |
| 23-27 | 1-3 | valid |
| 28-32 | 1-2 | valid |
| 33-37 | 1-7 | valid |
Valid episodes: 8-37 (30 total). Exclude 0-7 by index when scoring.
Eval-time config notes: fingertip slots mapped to match sotac's finger order (moving jaw first) via a processor-step flag; arm calibration = the bench file current at recording time. High-rate raw sensor sessions were recorded on the bench alongside but are not part of this dataset.
Scoring: stage rubric S0-S5 in the lerobotac dataset visualizer, as for the baseline evals. Companions: rollout_eval_tac_{pred,esn,esnpred}, baselines rollout_eval_A_71ep / B / Y.
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