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.

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