# 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.