Instructions to use OpenRAL/rskill-act-aloha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use OpenRAL/rskill-act-aloha with LeRobot:
- Notebooks
- Google Colab
- Kaggle
rskills/act-aloha/eval/ — benchmark results
aloha_transfer_cube.json is the ALOHA bimanual cube-transfer benchmark
result block for this rSkill. Validated against
openral_core.RSkillEvalResult
at load time by the rSkill loader and surfaced by openral benchmark report.
| Field | Value |
|---|---|
| Source | Zhao et al., 2023 — Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware (arxiv:2304.13705) |
| Benchmark | ALOHA bimanual cube transfer (gym_aloha/AlohaTransferCube-v0) |
| Robot | Trossen ALOHA (2 × 7-DoF + parallel grippers, 14-DoF action) |
| Reproduced locally? | ✗ — paper-only. tests/sim/test_aloha_bimanual_act_aloha.py runs a single episode for IO + latency verification but does not aggregate the 50-trial protocol. |
| Reproduce | just sim-act-aloha (single episode); raise --n-episodes 50 for the full paper protocol. |