Arena-Rosnav 2.0: A Development and Benchmarking Platform for Robot Navigation in Highly Dynamic Environments
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Abstract (arXiv)
Following up on our previous works, in this paper, we present Arena-Rosnav 2.0 an extension to our previous works Arena-Bench and Arena-Rosnav, which adds a variety of additional modules for developing and benchmarking robotic navigation approaches. The platform is fundamentally restructured and provides unified APIs to add additional functionalities such as planning algorithms, simulators, or evaluation functionalities. We have included more realistic simulation and pedestrian behavior and provide a profound documentation to lower the entry barrier. We evaluated our system by first, conducting a user study in which we asked experienced researchers as well as new practitioners and students to test our system. The feedback was mostly positive and a high number of participants are utilizing our system for other research endeavors. Finally, we demonstrate the feasibility of our system by integrating two new simulators and a variety of state of the art navigation approaches and benchmark them against one another. The platform is openly available at https://github.com/Arena-Rosnav.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 17 of its 33 references that are in the map. First posted on arXiv 20 Feb 2023.
Builds on
17 of 33 references.
References · 17
- 2018Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learningcited by 162
- 2017Socially Aware Motion Planning with Deep Reinforcement Learningcited by 128
- 2018Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learningcited by 101
- 2019Interactive Gibson Benchmark (iGibson 0.5): A Benchmark for Interactive Navigation in Cluttered Environmentscited by 89
- 2017Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learningcited by 81
- 2017PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planningcited by 64
- 2020Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Surveycited by 48
- 2020SEAN: Social Environment for Autonomous Navigationcited by 18
- 2020APPLD: Adaptive Planner Parameter Learning from Demonstrationcited by 17
- 2020NavRep: Unsupervised Representations for Reinforcement Learning of Robot Navigation in Dynamic Human Environmentscited by 12
- 2021Arena-Rosnav: Towards Deployment of Deep-Reinforcement-Learning-Based Obstacle Avoidance into Conventional Autonomous Navigation Systemscited by 12
- 2021SOCIALGYM: A Framework for Benchmarking Social Robot Navigationcited by 10
5 more
- 2014An Extensible Benchmarking Infrastructure for Motion Planning Algorithmscited by 9
- 2021All-in-One: A DRL-based Control Switch Combining State-of-the-art Navigation Plannerscited by 8
- 2022Arena-Bench: A Benchmarking Suite for Obstacle Avoidance Approaches in Highly Dynamic Environmentscited by 8
- 2020Deep-Reinforcement-Learning-Based Semantic Navigation of Mobile Robots in Dynamic Environmentscited by 4
- 2020MRPB 1.0: A Unified Benchmark for the Evaluation of Mobile Robot Local Planning Approachescited by 4
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