Genesis Howto

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Genesis is a comprehensive physics-based simulation platform that combines generative AI with universal physics engines to enable general-purpose robotics and embodied AI learning through automated environment generation and skill acquisition.
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How to Use Genesis

Install Prerequisites: Install Python version 3.9 or higher and PyTorch following the official PyTorch installation instructions from pytorch.org
Install Genesis: Run 'pip install genesis-world' in your terminal/command prompt to install the Genesis package
Import Required Modules: In your Python script, import Genesis modules. The exact imports will depend on which features you want to use (physics engine, rendering, etc.)
Set Up Simulation Environment: Create a simulation environment using Genesis's physics engine. You can load robot models using supported file formats like MJCF (.xml), URDF, .obj, .glb, .ply, or .stl
Configure Physics Parameters: Set up the physics parameters for your simulation including the type of solver (Rigid body, MPM, SPH, FEM, PBD, or Stable Fluid) depending on your needs
Add Objects and Materials: Add objects to your simulation environment and specify their material properties. Genesis supports various materials including rigid bodies, liquids, gases, deformable objects, and granular materials
Set Up Rendering: If visualization is needed, configure the rendering settings. Genesis supports both rasterization-based rendering and ray-tracing for photorealistic results
Run Simulation: Execute your simulation. Genesis can run at very high speeds - up to 43 million FPS on supported hardware (RTX 4090)
Access Documentation: Refer to the official documentation at genesis-world.readthedocs.io for detailed API references and tutorials for advanced features
Get Support: Use GitHub Issues for bug reports and feature requests, or GitHub Discussions for general questions and idea discussions

Genesis FAQs

Genesis is a comprehensive physics platform designed for general purpose Robotics, Embodied AI, and Physical AI applications. It combines a universal physics engine, a user-friendly robotics simulation platform, a photo-realistic rendering system, and a generative data engine that can transform natural language descriptions into various data modalities.

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