| --- |
| tags: |
| - OpenRAL |
| - rskill |
| - act |
| - lerobot |
| - aloha |
| - bimanual |
| - manipulation |
| license: mit |
| language: |
| - en |
| --- |
| |
| # rskill-act-aloha |
|
|
| > **OpenRAL rSkill** — ACT (Action Chunking Transformer) finetuned on |
| > the ALOHA bimanual cube-transfer task, packaged for `OpenRAL`. |
|
|
| This package wraps |
| [`lerobot/act_aloha_sim_transfer_cube_human`](https://huggingface.co/lerobot/act_aloha_sim_transfer_cube_human) |
| with a `rskill.yaml` manifest that adds capability checking, license |
| surfacing, latency budgets, and local registry integration. It does |
| **not** copy model weights. |
|
|
| ## Upstream model |
|
|
| | Field | Value | |
| | --- | --- | |
| | Source repo | [`lerobot/act_aloha_sim_transfer_cube_human`](https://huggingface.co/lerobot/act_aloha_sim_transfer_cube_human) | |
| | Paper | [arxiv:2304.13705](https://arxiv.org/abs/2304.13705) — *Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware* (Zhao et al., 2023) | |
| | License | MIT | |
| | Parameters | ~52 M (transformer encoder-decoder) | |
| | Action chunk | 100 | |
| | Benchmark | ALOHA bimanual cube-transfer (`gym-aloha`) | |
|
|
| > **Note.** The published checkpoint predates lerobot's |
| > `PolicyProcessorPipeline` migration and ships **without normalisation |
| > buffers**. See `tests/sim/test_aloha_bimanual_act_aloha.py` for the resulting |
| > numerical-contract caveats. |
|
|
| ## Supported robots |
|
|
| | Robot | Embodiment tag | Status | Notes | |
| | --- | --- | --- | --- | |
| | ALOHA bimanual (Trossen) — `gym-aloha` MuJoCo | `aloha`, `lerobot` | ✓ sim | 14-DoF (2 × 7-DoF arms with parallel grippers) | |
|
|
| ## Sensors required |
|
|
| | Key | Type | Resolution | Format | |
| | --- | --- | --- | --- | |
| | `observation.images.top` | RGB camera | 640 × 480 | `float32` | |
|
|
| ACT for ALOHA cube-transfer ships with a single top-down RGB stream. No |
| wrist or third-person view. |
|
|
| ## Manifest summary |
|
|
| | Field | Value | |
| | --- | --- | |
| | `name` | `OpenRAL/rskill-act-aloha` | |
| | `version` | `0.1.0` | |
| | `license` | `mit` | |
| | `role` | `s1` | |
| | `embodiment_tags` | `aloha`, `lerobot` | |
| | `runtime` / `quantization.dtype` | `pytorch` / `fp32` | |
| | `weights_uri` | `hf://lerobot/act_aloha_sim_transfer_cube_human` | |
| | `latency_budget.per_chunk_ms` | 25 ms (warm; bf16 autocast ≈ 12 ms on RTX 4070 Laptop) | |
| | `latency_budget.warmup_ms` | 5 000 ms | |
| | `latency_budget.load_ms` | 10 000 ms | |
| | `commercial_use_allowed` | `true` | |
|
|
| Full schema: `openral_core.RSkillManifest` — |
| `python/core/src/openral_core/schemas.py`. |
|
|
| ## Reproduction |
|
|
| ```bash |
| git clone https://github.com/OpenRAL/openral && cd OpenRAL |
| just bootstrap && uv sync --all-packages --group sim |
| |
| # End-to-end via the canonical SimEnvironment config: |
| just sim-act-aloha |
| # which runs: |
| # openral sim run --config scenes/benchmarks/act_aloha_transfer_cube.yaml --save-video |
| |
| # Sim test (real gym-aloha MuJoCo with contact dynamics): |
| uv run pytest tests/sim/test_aloha_bimanual_act_aloha.py -v -m sim |
| ``` |
|
|
| ## License |
|
|
| This rSkill package (`rskill.yaml`, `README.md`) is **MIT** to match the |
| upstream weights. Commercial use is allowed |
| (`commercial_use_allowed: true`). |
|
|
| ## See also |
|
|
| - [`robots/aloha_bimanual/README.md`](../../robots/aloha_bimanual/README.md) — RobotDescription manifest. |
| - [`scenes/benchmarks/act_aloha_transfer_cube.yaml`](../../scenes/benchmarks/act_aloha_transfer_cube.yaml) — paired SimEnvironment config. |
| - [`docs/reference/vla_compatibility.md`](../../docs/reference/vla_compatibility.md) — VLA × Robot × Sim matrix. |
|
|
