| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - reinforcement-learning |
| - grpo |
| - mujoco |
| - roboeval |
| - bimanual |
| - rollouts |
| - robotics |
| pretty_name: LocalModels ACT-bimanual GRPO rollouts |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # LocalModels / ACT-bimanual: GRPO rollouts |
|
|
| Rollouts saved by team LocalModels during the CoRL 2026 RoboEval challenge: 29 GRPO fine-tuning runs of ACT policies |
| on six bimanual tasks, **389,856 episodes** (318,256 successes, 75.8 million steps, 3.96 GB). Each episode is stored as |
| its environment seed plus every executed action, about 10 kB instead of about 40 MB rendered. With pinned BLAS the |
| simulator is deterministic, so an episode replays exactly and its camera frames can be re-rendered. |
|
|
| The final entry ships one learned model, LiftPot: `LiftPot/grpo_02` is the GRPO stage that produced it. The other runs |
| (including `LiftPot/grpo_01`) fine-tuned ACT models that the final entry does not use. |
|
|
| - Models and the official run: [Sa74ll/LocalModels-ACT-bimanual](https://huggingface.co/Sa74ll/LocalModels-ACT-bimanual) |
| - Code and report: [github.com/Sa74ll/RoboevalChallenge](https://github.com/Sa74ll/RoboevalChallenge) |
|
|
| ## Runs |
|
|
| Runs are numbered per task in the order of their GRPO round numbers. Rollouts use training seeds (10,000 and above): |
| 8 noisy rollouts per start state, Gaussian noise (sigma 0.2 or 0.3) on the normalized actions. |
|
|
| | Task | Run | Rounds | Episodes | Success | Notes | |
| |---|---|---|---|---|---| |
| | LiftPot | `grpo_01` | 31000-31116 | 11,232 | 75% | restart from GRPO v1 round 1150; was `lp_l1` | |
| | LiftPot | `grpo_02` | 37000-37199 | 19,200 | 84% | **trained the shipped LiftPot model** (snapshot round 37100: rounds 37000-37099, 9,600 episodes); was `lp_l2` | |
| | PackBox | `grpo_01` | 18045-18199 | 14,880 | 81% | was `gpb9500_t1` | |
| | PackBox | `grpo_02` | 20000-20086 | 8,352 | 78% | was `pb9500b_v2_5090` | |
| | PackBox | `grpo_03` | 30000-30133 | 12,864 | 84% | was `gpb_p1` | |
| | PackBox | `grpo_04` | 41000-41199 | 19,200 | 82% | task-progress reward bonus; was `pbtp_5090` | |
| | PackBox | `grpo_05` | 43000-43199 | 19,200 | 91% | was `pb_p3_5090` | |
| | PackBox | `grpo_06` | 44000-44261 | 16,768 | 90% | was `pb_p4_5090` | |
| | PackBox | `grpo_07` | 48000-48499 | 32,000 | 92% | was `pb_p5_5090` | |
| | PackBox | `grpo_08` | 49000-49249 | 24,000 | 94% | was `pb_p6` | |
| | PackBox | `grpo_09` | 50000-50316 | 30,432 | 94% | was `pb_p7_5090` | |
| | PickSingleBookFromTable | `grpo_01` | 34000-34199 | 19,200 | 82% | was `psb_k1` | |
| | PickSingleBookFromTable | `grpo_02` | 46000-46156 | 10,048 | 83% | was `psb_k2` | |
| | RotateValve | `grpo_01` | 45000-45089 | 5,760 | 86% | was `rv_r2` | |
| | RotateValve | `grpo_02` | 47000-47299 | 28,800 | 88% | was `rv_r3` | |
| | StackSingleBookShelf | `grpo_01` | 23000-23024 | 2,400 | 61% | action scale 0.85; was `ssbs160_v2` | |
| | StackSingleBookShelf | `grpo_02` | 28000-28009 | 960 | 76% | action scale 0.85; was `ssbsm1_v2` | |
| | StackSingleBookShelf | `grpo_03` | 35000-35199 | 19,200 | 88% | action scale 0.85; was `ssbsm2_v2` | |
| | StackSingleBookShelf | `grpo_04` | 36000-36199 | 19,200 | 90% | action scale 0.85; was `ssbsm2_v2b` | |
| | StackTwoBlocks | `grpo_01` | 16045-16199 | 14,880 | 58% | was `s2bbr_v2b` | |
| | StackTwoBlocks | `grpo_02` | 17060-17199 | 8,960 | 60% | was `s2bbr_a3` | |
| | StackTwoBlocks | `grpo_03` | 21075-21149 | 7,200 | 58% | was `s2bbr_v2b_f5090` | |
| | StackTwoBlocks | `grpo_04` | 22075-22174 | 9,600 | 60% | was `s2bbr_a4` | |
| | StackTwoBlocks | `grpo_05` | 25075-25086 | 1,152 | 59% | privileged value baseline; was `s2bbr_a5` | |
| | StackTwoBlocks | `grpo_06` | 26000-26161 | 15,552 | 63% | privileged value baseline; was `s2bbr_a5b` | |
| | StackTwoBlocks | `grpo_07` | 27000-27079 | 7,680 | 53% | was `s2bbr_a6` | |
| | StackTwoBlocks | `grpo_08` | 29000-29054 | 5,280 | 54% | was `s2bbr_a6b` | |
| | StackTwoBlocks | `grpo_09` | 32000-32057 | 5,568 | 57% | was `s2bbr_a7` | |
| | StackTwoBlocks | `grpo_10` | 33000-33002 | 288 | 61% | was `s2b_a8` | |
|
|
| Notes: ShelfBook runs executed the policy's actions scaled by 0.85 (the stored actions are the executed ones). All |
| StackTwoBlocks rewards include shaping terms computed from simulator positions, and two of its runs used a value |
| baseline from simulator state; the stored data are still seeds and actions only. |
|
|
| ## Format |
|
|
| ``` |
| <Task>/<run>/log.jsonl one line of GRPO metrics per round |
| <Task>/<run>/successes/it<N>.npz round N, episodes that succeeded (+ it<N>.json) |
| <Task>/<run>/failures/it<N>.npz round N, all other episodes (+ it<N>.json) |
| ``` |
|
|
| - `it<N>.npz`: `actions` (float32, steps x 14: end-effector deltas `dp_L dr_L dp_R dr_R g_L g_R` at 20 Hz) and |
| `offsets` (episode k is `actions[offsets[k]:offsets[k+1]]`). |
| - `it<N>.json`: one record per episode: `seed`, `steps`, `term` (how it ended), `success`, `tp` (task progression), |
| `R` (GRPO reward), `iter`, `prefix_t` (actions replayed from a logged episode before the rollout; 0 for a fresh start). |
|
|
| To replay an episode: `env.reset(seed=seed)`, then step every stored action (the first is a one-step open-gripper |
| no-op). Exact replay needs RoboEval at tag `corl2026-challenge`, MuJoCo 3.3.3 and pinned BLAS |
| (`OPENBLAS_CORETYPE=Haswell OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1 MKL_CBWR=COMPATIBLE`). |
|
|
| ## License |
|
|
| Apache-2.0. No demonstration data or rendered frames are included. |
|
|
