Orcahand

OrcaHand

Full-stack skill for the ORCA Hand — 17-DOF tendon-driven dexterous robotic hand. Compounds on agentic-control-kernel (plant/shield/trace) and bstack (governance).

Plant Interface

Dual-backend: physical (orca_core) and simulated (orca_sim) share identical typed schemas.

observe() → OrcaHandState (schemas/orcahand-state.schema.json)
  measured:
    joint_positions: {thumb_mcp, thumb_abd, thumb_pip, thumb_dip,
                      index_abd, index_mcp, index_pip,
                      middle_abd, middle_mcp, middle_pip,
                      ring_abd, ring_mcp, ring_pip,
                      pinky_abd, pinky_mcp, pinky_pip, wrist}  # degrees
    motor_currents:      17 motors, mA
    motor_temperatures:  17 motors, celsius
    tactile_readings:    per-sensor [fx, fy, fz] in N (touch model only)
  estimated:
    grasp_state:  "open" | "contact" | "secured" | "slipping"
  context:
    backend: "physical" | "simulated"
    control_mode: "position" | "current" | "current_based_position"
    torque_enabled: bool

apply(action) → ActuationResult (schemas/orcahand-action.schema.json)
  directive_type:  setpoint_update | experiment_request | mode_switch
  target_controller: "orca_core" | "orca_sim"
  payload:
    joint_targets: {joint_name: degrees}   # partial dict OK
    num_steps: 25, step_size: 0.001s
    grasp_type: "power" | "precision" | "pinch"

reset(seed?) → neutral position (physical) or env.reset (simulated)

constraints():
  joint_roms: per-joint [min_deg, max_deg] from config.yaml
  max_current: 200mA, max_temperature: 70°C

Safety Shields

Implements kernel SafetyShield contract: filter(), feasible(), fallback().

Emergency fallback: hand.disable_torque() — hand goes limp. Safe due to popping joints. Cascade: filter() -> feasible() -> if infeasible -> emergency fallback + alert outer loop.

Multi-Rate Loop Mapping

SERVO (ms)     Dynamixel PID firmware. Agent never touches this.
     |
MID (10-100ms) Retargeter @ 30Hz / RL policy @ 60Hz / Replay @ 60Hz
               Safety shields run HERE: ROM clamp + current check per frame
     |
OUTER (sec)    LLM supervisory: grasp strategy, mode switch, task goals
               Outputs ControlDirective -> mid-loop controller
     |
META (min-day) EGRI: problem-spec -> train in sim -> evaluate -> promote to physical
               Runs on remote GPU, validated on local macOS

Quick Starts

• Build a hand: Read references/hardware-build.md — BOM, 3D printing, Dynamixel sourcing, assembly, wiring
• Simulate: Read references/simulation-setup.md — pip install orca_sim, MuJoCo on macOS, environment catalog
• Teleoperate: Read references/teleoperation.md — AVP / Rokoko / MediaPipe -> retargeter -> hand
• Train RL policies: Read references/rl-training.md — local CPU/MPS or remote GPU, reward design
• Improve controllers: Read references/egri-controller-loop.md — EGRI problem-spec, evaluator, promotion

Scope Router

Load the relevant reference based on user intent. Max 3 references at once.

Scripts

• scripts/orcahand_init.py — Bootstrap workspace: clone repos, install deps, detect serial, generate .control/plant.yaml
• scripts/orcahand_check.py — Health check for bstack integration (JSON output, exit 0/1)

Schemas

• schemas/orcahand-state.schema.json — extends kernel state.schema.json
• schemas/orcahand-action.schema.json — extends kernel action.schema.json
• schemas/orcahand-trace.schema.json — extends kernel trace.schema.json

Templates

• assets/templates/problem-spec.orcahand.yaml — EGRI template for grasp optimization
• assets/templates/config.orcahand.yaml — starter config for new hand builds