🤖
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.
安全通过
💬Prompt
技能说明
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
如何使用「JARVIS AI Skills」?
- 打开小龙虾AI(Web 或 iOS App)
- 点击上方「立即使用」按钮,或在对话框中输入任务描述
- 小龙虾AI 会自动匹配并调用「JARVIS AI Skills」技能完成任务
- 结果即时呈现,支持继续对话优化