Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering
This provides a high-fidelity simulation tool for robotics researchers to test perception, control, and navigation algorithms in diverse and adverse conditions, facilitating sim-to-real transfer.
The paper tackles the challenge of achieving both photorealistic rendering and accurate physics in robotics simulation by presenting the Unreal Robotics Lab, which integrates Unreal Engine's rendering with MuJoCo's physics, enabling realistic perception and physical interactions for benchmarking vision-based robotics applications.
High-fidelity simulation is essential for robotics research, enabling safe and efficient testing of perception, control, and navigation algorithms. However, achieving both photorealistic rendering and accurate physics modeling remains a challenge. This paper presents a novel simulation framework--the Unreal Robotics Lab (URL) that integrates the Unreal Engine's advanced rendering capabilities with MuJoCo's high-precision physics simulation. Our approach enables realistic robotic perception while maintaining accurate physical interactions, facilitating benchmarking and dataset generation for vision-based robotics applications. The system supports complex environmental effects, such as smoke, fire, and water dynamics, which are critical for evaluating robotic performance under adverse conditions. We benchmark visual navigation and SLAM methods within our framework, demonstrating its utility for testing real-world robustness in controlled yet diverse scenarios. By bridging the gap between physics accuracy and photorealistic rendering, our framework provides a powerful tool for advancing robotics research and sim-to-real transfer.