[2504.14135] Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering

[2504.14135] Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering

arXiv - Machine Learning 4 min read

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Abstract page for arXiv paper 2504.14135: Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering

Computer Science > Robotics arXiv:2504.14135 (cs) [Submitted on 19 Apr 2025 (v1), last revised 7 Apr 2026 (this version, v3)] Title:Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering Authors:Jonathan Embley-Riches, Jianwei Liu, Simon Julier, Dimitrios Kanoulas View a PDF of the paper titled Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering, by Jonathan Embley-Riches and 3 other authors View PDF HTML (experimental) Abstract: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 advanced rendering capabilities of the Unreal Engine 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 to 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 bridgi...

Originally published on April 08, 2026. Curated by AI News.

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