--- 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.