🧪 Skills
JARVIS AI Skills
Control robotic arms and grippers via voice or code with OpenClaw, supporting precise 6-DOF movement, force sensing, collision detection, and simulation.
v1.0.0
Description
Robotic Control Skill (OpenClaw)
Overview
The Robotic Control skill integrates OpenClaw for physical robotic arm and gripper manipulation through voice commands and programmatic control.
Slug
robotic-control
Features
- Robotic arm movement (6-DOF)
- Gripper grab/release operations
- Precise positioning and orientation
- Force/torque sensing
- Collision detection and safety
- Action sequence execution
- Hardware auto-detection
- Simulation mode support
Implementation
- Module:
openclaw_control.py - Primary Library:
OpenClaw SDK - Communication: USB Serial, Ethernet, ROS
Configuration
from openclaw_control import init_claw, get_claw
# Initialize claw
claw = init_claw()
# Control operations
claw.grab(force=50.0)
claw.move_to(10, 20, 30)
claw.release()
Voice Commands
- "Jarvis, grab the object"
- "Jarvis, move to 10 20 30"
- "Jarvis, rotate 45 degrees"
- "Jarvis, release"
- "Jarvis, return to home"
- "Jarvis, claw status"
Hardware Support
- Universal Robots (UR)
- ABB Robotics
- KUKA
- Stäubli
- Custom embedded systems
Performance
- Reach: 2-3 meters (model-dependent)
- Payload: 3-500 kg (model-dependent)
- Precision: ±0.03-0.1 mm
- Speed: 1-7000 mm/s
- Response Time: <10ms
Dependencies
- openclaw
- pyserial
- numpy
Author
Aly-Joseph
Version
2.0.0
Last Updated
2026-01-31
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