A versatile skill for controlling Unitree mobile robots and AI stereo cameras through instant messaging platforms.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-robotics
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install openclaw-robotics using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Unitree Robot Controller?
The Unitree Robot Controller is a specialized tool designed to bridge the gap between AI agent platforms and physical robotics. It enables developers and enthusiasts to command a wide range of mobile robots—including quadruped, bipedal, and humanoid models—using standard instant messaging platforms. This skill simplifies the complex task of robot telemetry and command execution, providing a unified interface for the next generation of Openclaw Skills focused on physical hardware interaction.
By abstracting the underlying communication protocols, this skill allows users to focus on high-level logic and task automation. Whether you are managing a fleet of quadrupeds or a single humanoid robot, the controller provides the necessary hooks to integrate physical movement into your AI-driven workflows.
Unitree Robot Controller Use Cases
- Remote monitoring and control of Unitree Go2 or G1 robots via messaging apps like WeCom.
- Integrating AI stereo camera depth sensing into automated visual inspection workflows.
- Rapid prototyping of robot movement sequences using standardized Python scripts.
- Deploying humanoid robots for research and development tasks with minimal infrastructure setup.
How Unitree Robot Controller Works
- Initialize the environment with specific robot hardware codes and the preferred IM platform configuration.
- Establish a secure communication bridge between the AI agent and the robot's onboard control system.
- Send high-level movement, orientation, or sensor-query commands through the skill execution engine.
- Receive real-time telemetry data and visual feedback from the robot or the Insight9 sensor for processing.
Unitree Robot Controller Setup
To get started with this skill, ensure you have Python 3.8 or higher. Install the required dependencies using pip:
pip install numpy unitree-robot-skill
Once installed, configure your IM platform credentials and ensure your robot hardware is accessible on your local network or via a secure gateway.
Unitree Robot Controller Data Schema & Taxonomy
The skill utilizes a structured mapping for hardware identification and command execution. The following table highlights the primary data categories:
| Category | Supported Identifiers |
|---|---|
| Quadruped Models | unitree_go1, unitree_go2 |
| Humanoid Models | unitree_g1, unitree_h1 |
| AI Sensors | insight9 (Stereo Camera) |
| IM Platforms | wecom, and more coming soon |
| Commands | movement (forward, turn), telemetry (status, imu) |
Unitree Robot Controller Advanced Features
- Multi-robot fleet support for heterogeneous groups including upcoming wheeled and aerial robots.
- Native integration with Looper Robotics Insight9 AI Stereo Camera for advanced RGB-D data acquisition.
- Roadmap support for TinyNav path planning to enable autonomous obstacle avoidance.
- Extensible execution framework that pairs perfectly with other Openclaw Skills for complex hardware automation.
SKILL.md
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