VLArm

About

VLArm is designed to replicate Google DeepMind's Vision-Language-Action (VLA) model, transforming an existing robot, specifically HuggingFace's SO-101 arm, into an intelligent system capable of making decisions autonomously. By integrating a locally-running MCP server with a Large Language Model (LLM) from Ollama, this project enables the robotic arm to execute complex actions based on natural language commands. It lays the groundwork for advanced industrial applications where robots can interpret and respond to human instructions, with future plans to incorporate live vision and listening capabilities.

Key Features

• Language-based control for robotic arm actions
• Configurable MCP server based on Anthropic's open-source protocol
• Integration with local Large Language Models (Ollama) for tool-use
• Includes 3D printable designs for the robot arm casing
• 0 GitHub stars
• Autonomous decision-making for robotic arms via local LLM

Use Cases

• Industrial automation with intelligent robotic arms
• Developing autonomous robots capable of language-based interaction
• Robotics research and experimentation with VLA models