chore: canonical naming migration

fc9f3ca verified 2 months ago

3.46 kB

name: smolvla-maniskill-franka
description: >-
  S1 Vision-Language-Action policy. Capabilities: pick, grasp on cube. SmolVLA
  (0.45 B, lerobot/smolvla_base) finetuned on
  Calvert0921/SmolVLA_LiftCube_Franka_1000 (1000 demos of a Franka Panda lifting
  a cube in ManiSkill3 SAPIEN). Action chunks of length 50 across overhead +
  wrist RGB views and a 9-D Franka qpos state. Runs end-to-end on ManiSkill3
  PickCube-v1 with a live SAPIEN viewer via `openral sim run --view`. Discovery
  view of an OpenRAL rSkill — NOT directly runnable by an agent harness; it runs
  via rSkill.from_pretrained + the robot HAL.
metadata:
  openral_rskill: true
  schema_version: 0.1
  rskill_id: OpenRAL/rskill-smolvla-franka_panda-maniskill3-bf16
  manifest: ./rskill.yaml
  role: s1
  kind: vla
  model_family: smolvla
  embodiment_tags:
    - franka_panda
  actions:
    - pick
    - grasp
  objects:
    - cube
  scenes:
    - tabletop
  sensors_required:
    - rgb:observation.images.camera1
    - rgb:observation.images.camera2
  state_dim: 9
  action_dim: 8
  runtime: pytorch
  quantization: bf16/pytorch
  chunk_size: 50
  n_action_steps: 50
  latency_budget:
    per_chunk_ms: 200
  license_code: Apache-2.0
  license_weights: apache-2.0
  weights_uri: hf://Calvert0921/smolvla_franka_liftcube_1000
  source_repo: hf://Calvert0921/smolvla_franka_liftcube_1000
  paper_url: https://arxiv.org/abs/2506.01844

smolvla-maniskill-franka — rSkill discovery view

Generated view, not a hand-written skill. This SKILL.md is a discovery-only mirror of rskill.yaml, produced by tools/generate_rskill_skillmd.py. It lets tools that read the standard agent-skill format find and reason about this OpenRAL rSkill. The rskill.yaml manifest is the single source of truth (CLAUDE.md §1.3). Do not edit by hand — edit the manifest and regenerate.

What it is

An OpenRAL Vision-Language-Action policy (role: s1, kind: vla). SmolVLA (0.45 B, lerobot/smolvla_base) finetuned on Calvert0921/SmolVLA_LiftCube_Franka_1000 (1000 demos of a Franka Panda lifting a cube in ManiSkill3 SAPIEN). Action chunks of length 50 across overhead + wrist RGB views and a 9-D Franka qpos state. Runs end-to-end on ManiSkill3 PickCube-v1 with a live SAPIEN viewer via openral sim run --view.

Capabilities

Verbs: pick · grasp
Objects: cube
Scenes: tabletop
Embodiments: franka_panda

Why this is discovery-only

An agent skill is natural-language instructions loaded into an LLM's context. An rSkill is an executable artifact: it carries a typed capability/embodiment contract, model weights, a runtime, and a license/provenance gate — none of which fit in freeform markdown. So an agent can use this view to select the right skill, but cannot execute it by loading this file. Execution always goes through the OpenRAL loader and the robot HAL.

License

Code: Apache-2.0.
Weights: apache-2.0 — permissive / commercial-use OK

How to actually run it (not via an agent harness)

from openral_rskill import rSkill

skill = rSkill.from_pretrained("OpenRAL/rskill-smolvla-franka_panda-maniskill3-bf16")
# the loader validates embodiment / sensors / runtime / quantization against the target
# RobotDescription and enforces the weight-license gate before any weights load.

See rskill.yaml for the authoritative, validated manifest.