Datasets:
rollout_eval_B_50ep
Real-robot evaluation rollouts of an ACT policy on the SO-101, red foam ball pick-and-place. Recorded 5 September 2026. This is evaluation data, not training data — every episode is the policy acting autonomously, no teleoperation.
Policy under test
| Checkpoint | Jingyi-Z/act-sotac-runB-ep21-70 (step 100000) |
| Training data | Jingyi-Z/sotac episodes 21–70 (50 episodes), tactile column removed |
| Inputs | observation.state (6) + observation.images.top + observation.images.wrist — no tactile |
| Training | 100k steps, batch 8, seed 1000, lr 1e-5, ResNet18, chunk 100, no augmentation, MEAN_STD normalisation |
Sibling policies evaluated under the same protocol: Jingyi-Z/act-sotac-runA-ep0-70 (sotac ep 0–70, 71 episodes,
rollouts in Jingyi-Z/rollout_eval_A_71ep) and Yu-Zhou-Wang/act_so_101_red_foam_ball (sotac ep 0–20, 21 episodes).
A is the union of B and Y; B and Y are disjoint.
Rollout setup
| Robot | SO-101 follower, calibration id so_sensor_follower |
| Cameras | wrist = Innomaker U20CAM-1080p, top = icspring; both 640×480 @ 30 fps |
| Control | 30 fps, sync inference, lerobot-rollout --strategy.type=episodic |
| Episode | 60 s policy execution, 30 s reset between episodes |
| Task string | "Pick up the red foam ball and place it into the bowl" |
| Recorder | lerobot (a0eval env), push_to_hub=false, uploaded afterwards |
Scene design
Seven marked points on the desk. A scene is a (bowl point, ball point) pair, written bowl-ball.
Each scene is run 5 times in a row without moving anything — the ball is returned to its mark
during the 30 s reset. The desk marks are identical to those used for rollout_eval_A_71ep
(point 2 at its final position, point 7 included).
Bowl fixed at point 1, ball at each other point.
| Scene | Episodes | Bowl–Ball | Status |
|---|---|---|---|
| 1 | 0–4 | 1-6 | valid |
| 2 | 5–9 | 1-5 | valid |
| 3 | 10–14 | 1-4 | valid |
| 4 | 15–19 | 1-3 | valid |
| 5 | 20–24 | 1-2 | valid |
| 6 | 25, 26, 28, 29, 30 | 1-7 | valid |
| — | 27 | (1-2) | discard — ball was placed on point 2 by mistake during the 1-7 block |
31 episodes on disk, 30 valid. Episode 27 is kept for completeness but must be excluded from any score: the ball was on point 2 rather than point 7, so it belongs to neither scene. Episode 30 was recorded as a replacement so that scene 1-7 has five valid episodes. Point 2 is a known hard reach for the arm and is kept deliberately — all three policies face the same point.
Scoring
Scored offline from the recordings, not live, using the lab rubric: score = highest stage reached,
not additive — S0 freeze 0 · S1 reach 0.2 · S2 grasp 0.4 · S3 transport 0.7 · S4 release 0.8 ·
S5 ball in bowl 1.0 — plus one primary failure mode (F0_none … F8_other). Scores live in the
SO101_eval_labeling_workbook_act_v2.xlsx workbook, not in this repo.
Loading
from lerobot.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("Jingyi-Z/rollout_eval_B_50ep")
valid = [e for e in range(ds.num_episodes) if e != 27]
scene_of = {**{e: "1-6" for e in range(0, 5)}, **{e: "1-5" for e in range(5, 10)},
**{e: "1-4" for e in range(10, 15)}, **{e: "1-3" for e in range(15, 20)},
**{e: "1-2" for e in range(20, 25)}, **{e: "1-7" for e in (25, 26, 28, 29, 30)}}
Notes
- Camera device indices on the recording machine were
0(wrist) and2(top); indices1and3are the cameras' metadata nodes and are not capture devices. --display_datawas off during recording: an X-forwarded Rerun viewer stalled the control loop to 3 Hz and froze the arm. Every frame is in the dataset regardless.
- Downloads last month
- 226