Training VLAs for coordinated manipulation and navigation tasks.
About This Project
An Isaac Sim 5.1.0 environment for the Spot robot with arm, designed to train multiple VLAs (Vision-Language-Action models) for separate control of legs and the arm.
README
This project creates a simulation environment for Boston Dynamics' Spot robot with an attached arm, enabling research on multi-agent control policies.
Key Features
- Isaac Sim 5.1.0 - NVIDIA's robotics simulation platform
- Spot Robot - Simulation of Boston Dynamics' quadruped robot
- Multi-Agent Architecture - Separate VLAs for leg and arm control
- Vision-Language-Action Models - Generalist robotic control
Research Goals
- Train separate policies for locomotion and manipulation
- Explore multi-agent coordination in embodied AI
- Develop VLA-based robot control systems
Technical Details
The environment leverages NVIDIA's Isaac Sim for physics-accurate simulation, enabling development of control policies that can potentially transfer to real hardware.