Demonstrating Arena 5.0: A Photorealistic ROS2 Simulation Framework for Developing and Benchmarking Social Navigation


Linh Kästner, Volodymyr Shcherbyna, Harold Soh, Giang Nguyen Huu Truong, Do Duc Anh, Ton Manh Kien, Tim Seeger, Ahmed Martban, Vu Thanh Lam, Nguyen Quoc Hung, Pham Thai Hoang Tung, Tran Dang An, Eva Wiese, Maximilian Ho-Kyoung Schreff

Paper ID 92

Session 9. HRI

Poster Session (Day 3): Monday, June 23, 12:30-2:00 PM

Abstract: Building upon the foundations laid by our previous work, this paper introducesArena 5.0, the fifth iteration of our framework for robotics social navigation development and benchmarking. Arena 5.0 provides three main contributions: 1) The complete integration of NVIDIA Isaac Gym, enabling photorealistic simulations and more efficient training. It seamlessly incorporates Isaac Gym into the Arena platform, allowing the use of existing modules such as randomized environment generation, evaluation tools, ROS2 support, and the integration of planners, robot models, and APIs within Isaac Gym. 2) A comprehensive benchmark of state-of-the-art social navigation strategies, evaluated on a diverse set of generated and customized worlds and scenarios of varying difficulty levels. These benchmarks provide a detailed assessment of navigation planners using a wide range of social navigation metrics. 3) An extensive set of modules for specified and highly customizable scenario generation and task planning facilitating improved and customizable generation of social navigation scenarios, such as emergency and rescue situations. The platform’s performance was evaluated by generating the aforementioned benchmark and through a comprehensive user study, demonstrating significant improvements in usability and efficiency compared to previous versions. Arena 5.0 is open source and available at https://github.com/Arena-Rosnav.