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Agibot X1 Train
Overview :
The Agibot X1, developed by Agibot, is a modular humanoid robot with high degrees of freedom, utilizing the Agibot open-source framework AimRT as middleware and employing reinforcement learning for motion control. This project includes the reinforcement learning training code used by Agibot X1, which can be combined with the inference software provided by Agibot X1 for real robots and simulation walking debugging, or importing other robot models for training.
Target Users :
The target audience includes researchers, developers, and enthusiasts in robotics, particularly those interested in the application of reinforcement learning for robot control. Agibot X1 offers a modular platform that allows users to train robots to perform various tasks using reinforcement learning methods. It is also customizable and extensible, making it suitable for research and development work.
Use Cases
Researchers use Agibot X1 to study the stability of robot walking.
Developers utilize the Agibot X1 codebase to create training environments for other types of robots.
Educators use Agibot X1 as a teaching tool to demonstrate the application of reinforcement learning in robot control to students.
Features
Motion control for robots using reinforcement learning
Support for walking debugging in both real robots and simulation environments
Ability to import other robot models for training
Provides detailed installation and usage instructions
Supports control using the Logitech F710 game controller
Allows users to add new environments and robot models
Uses Mujoco for sim2sim validation
How to Use
1. Install Python 3.8 virtual environment
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2. Install PyTorch 1.13 and CUDA 11.7
3. Install Numpy-1.23
4. Download and install Isaac Gym Preview 4
5. Clone the Agibot X1 code repository and install dependencies
6. Use the training script to train the model
7. Use a game controller to control the robot for simulation or real-world testing
8. If needed, add new environments or robot models to the project
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