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GB-Power-Market-JJ jarvis-skills

Robotic Control Skill (OpenClaw)

install
source · Clone the upstream repo
git clone https://github.com/GeorgeDoors888/GB-Power-Market-JJ
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/GeorgeDoors888/GB-Power-Market-JJ "$T" && mkdir -p ~/.claude/skills && cp -r "$T/openclaw-skills/skills/aly-joseph/jarvis-skills" ~/.claude/skills/georgedoors888-gb-power-market-jj-jarvis-skills && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/GeorgeDoors888/GB-Power-Market-JJ "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/openclaw-skills/skills/aly-joseph/jarvis-skills" ~/.openclaw/skills/georgedoors888-gb-power-market-jj-jarvis-skills && rm -rf "$T"
manifest: openclaw-skills/skills/aly-joseph/jarvis-skills/SKILL.md
source content

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