GibsonEnv
A virtual environment simulator for training embodied AI agents with real-world perception and physics, featuring domain transfer to real robots.
What is GibsonEnv?
Gibson Environment is a virtual simulation platform for training embodied AI agents, such as robots, in realistic 3D environments scanned from the real world. It addresses the challenges of costly and slow real-world robot training by providing a fast, scalable simulator with integrated physics and perception. The platform includes a domain adaptation mechanism called Goggles to help transfer learned policies from simulation to real robots.
Researchers and developers working on embodied AI, reinforcement learning for robotics, and computer vision for autonomous agents. It is particularly useful for those needing high-fidelity simulation with real-world scene complexity.
Gibson offers unique real-world scene datasets, a built-in domain transfer capability (Goggles), and high-performance rendering, making it a preferred choice for simulation-to-real-world robotics research over generic game engines or simpler simulators.
Overview
Gibson Environments: Real-World Perception for Embodied Agents
Use Cases
Best For
- Training reinforcement learning agents for navigation in complex indoor environments
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
