orcahand · git:20260628.9edbf07 · 2026-06-28 · sha256 f754f9b157073b3e
orcahand git:20260628.9edbf07A
Immutable. This exact content is served forever at /api/v1/blob/f754f9b157073b3e.
---
name: orcahand
category: robotics
description: >
Full-stack skill for the ORCA Hand — 17-DOF tendon-driven robotic hand
(ETH Zurich). Implements agentic-control-kernel Plant interface with typed
schemas, safety shields, multi-rate loops. Lifecycle: 3D print + assembly,
MuJoCo sim (orca_sim), RL training (macOS + remote GPU), teleoperation
(AVP/Rokoko/MediaPipe via orca_retargeter), sim-to-real, EGRI improvement.
Use when: building/assembling OrcaHand, orca_sim environments, teleoperating,
training grasp policies, sim-to-real transfer, control-kernel Plant schemas,
EGRI loops. Triggers: "orcahand", "orca_core", "orca_sim", "dexterous hand",
"robotic hand", "tendon-driven", "dynamixel hand", "hand simulation",
"teleoperate hand", "grasp policy", "sim-to-real hand", "3d print hand".
---
# OrcaHand
Full-stack skill for the [ORCA Hand](https://orcahand.com/) — 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()`.
| Shield | Invariant | filter() | feasible() |
|--------|-----------|----------|------------|
| Joint ROM | Targets within bounds | Clamp to valid range | >= 1 joint can move |
| Max Current | < 200mA per motor | Disable torque, alert | Current below threshold |
| Temperature | < 70°C per motor | Disable torque, cooldown | All motors < 65°C |
| Velocity | < safe joint velocity | Reduce step_size | Velocity achievable |
| Tactile | Force < sensor max | Release grasp, back off | Force within range |
**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](references/hardware-build.md) — BOM, 3D printing, Dynamixel sourcing, assembly, wiring
- **Simulate**: Read [references/simulation-setup.md](references/simulation-setup.md) — `pip install orca_sim`, MuJoCo on macOS, environment catalog
- **Teleoperate**: Read [references/teleoperation.md](references/teleoperation.md) — AVP / Rokoko / MediaPipe -> retargeter -> hand
- **Train RL policies**: Read [references/rl-training.md](references/rl-training.md) — local CPU/MPS or remote GPU, reward design
- **Improve controllers**: Read [references/egri-controller-loop.md](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.
| Intent | Keywords | Reference |
|--------|----------|-----------|
| Build hand | build, print, assemble, BOM, servo, wire | `hardware-build.md` |
| Calibrate | calibrate, tension, neutral, config.yaml, serial | `calibration-pipeline.md` |
| Simulate | simulate, mujoco, orca_sim, gymnasium, render | `simulation-setup.md` |
| Train | train, RL, PPO, SAC, reward, policy, GPU | `rl-training.md` |
| Teleoperate | teleoperate, retarget, vision pro, rokoko, mediapipe | `teleoperation.md` |
| Sim-to-real | sim-to-real, domain randomization, joint reorder | `sim-to-real.md` |
| EGRI | improve, optimize, EGRI, problem-spec, evaluator | `egri-controller-loop.md` |
| API | OrcaHand class, set_joint_pos, REST API, joint names | `api-reference.md` |
| Install | install, clone, dependencies, which repo, version | `dependency-graph.md` |
| Debug | servo not found, segfault, drift, error, stuck | `troubleshooting.md` |
## 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