Instructions to use OpenRAL/rskill-act-aloha-insertion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use OpenRAL/rskill-act-aloha-insertion with LeRobot:
- Notebooks
- Google Colab
- Kaggle
| # rSkill manifest — OpenRAL packaging format V1 (CLAUDE.md §6.4) | |
| # Wraps: lerobot/act_aloha_sim_insertion_human (MIT) | |
| # Paper: Zhao et al., 2023 — Action Chunking Transformer. | |
| # | |
| # Sibling of skills/act-aloha (which wraps the transfer-cube checkpoint). | |
| # This package targets the harder bimanual peg-in-socket *insertion* task | |
| # from the same paper. Both skills share the ALOHA 14-DoF action space and | |
| # the single 480x640 top camera contract. | |
| schema_version: "1" | |
| name: "AdrianLlopart/rskill-act-aloha-insertion" | |
| version: "0.1.0" | |
| license: "mit" | |
| role: "s1" | |
| model_family: "act" | |
| embodiment_tags: | |
| - "aloha" | |
| capabilities_required: {} | |
| sensors_required: | |
| - modality: "rgb" | |
| vla_feature_key: "observation.images.top" | |
| min_width: 640 | |
| min_height: 480 | |
| # Output side (ADR-0013). For the canonical aloha bimanual embodiment the | |
| # loader auto-fills n_dof (14) + vla_action_key from | |
| # robots/aloha_bimanual/robot.yaml. | |
| actuators_required: | |
| - kind: "joint_position" | |
| runtime: "pytorch" | |
| quantization: | |
| dtype: "fp32" | |
| backend: "pytorch" | |
| weights_uri: "hf://lerobot/act_aloha_sim_insertion_human" | |
| chunk_size: 100 | |
| latency_budget: | |
| # Same ACT architecture as the cube-transfer sibling; reference-host | |
| # measurements match within noise. The 25 ms ceiling keeps the | |
| # canonical tolerance_pct=100 → 50 ms test ceiling. | |
| per_chunk_ms: 25.0 | |
| warmup_ms: 5000.0 | |
| load_ms: 10000.0 | |
| fallback_skill_id: null | |
| # Headline success rate from skills/act-aloha-insertion/eval/aloha_insertion.json. | |
| benchmarks: | |
| aloha_insertion: 0.20 | |
| policy_id: "act" | |
| paper_url: "https://arxiv.org/abs/2304.13705" | |
| source_repo: "hf://lerobot/act_aloha_sim_insertion_human" | |
| description: > | |
| ACT (~52M params, chunk=100) finetuned on the ALOHA bimanual | |
| sim-insertion demonstration set. Like the transfer-cube sibling, the | |
| published checkpoint predates lerobot's PolicyProcessorPipeline | |
| migration and ships without normalisation buffers. Insertion is the | |
| harder ALOHA task in the original paper; the 0.20 success rate | |
| reflects that. | |