tags:
- OpenRAL
- rskill
- act
- lerobot
- aloha
- bimanual
- manipulation
- insertion
license: mit
language:
- en
rskill-act-aloha-insertion
OpenRAL rSkill (custom example) — ACT (Action Chunking Transformer) finetuned on the ALOHA bimanual peg-insertion task, packaged for
OpenRAL.
This package wraps
lerobot/act_aloha_sim_insertion_human
with a rskill.yaml manifest that adds capability checking, license
surfacing, latency budgets, and local registry integration. It does
not copy model weights.
It is the harder sibling of rskill-act-aloha (cube
transfer) and demonstrates how a single packaging format covers multiple
task-specific checkpoints from the same paper. The runnable demo lives at
examples/sim/custom_act_aloha_insertion.yaml and is wired into the
top-level just sim-custom recipe.
Upstream model
| Field | Value |
|---|---|
| Source repo | lerobot/act_aloha_sim_insertion_human |
| Architecture | Action Chunking Transformer (~52M params, chunk=100) |
| Task | gym-aloha AlohaInsertion-v0 (bimanual peg-in-socket) |
| License | MIT |
| Paper | Zhao et al., 2023 — Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware (arXiv 2304.13705) |
Why no eval/ block?
This skill is shipped as a custom-example package, not as a
reproduced benchmark entry. The paper's headline number for sim ALOHA
insertion is markedly lower than the cube-transfer figure (the task is
harder and the upstream protocol uses different camera intrinsics). We
deliberately omit eval/ rather than copy paper numbers without an
internal reproduction; per CLAUDE.md §6.4 that omission must be
documented — this section is that documentation. Add eval/aloha_insertion.json
once a local reproduction lands.
Run it
just sim-custom
…which is equivalent to:
MUJOCO_GL=egl uv run --group sim ral sim run \
--config examples/sim/custom_act_aloha_insertion.yaml \
--save-video example_videos