# Arena-Rosnav 2.0: A Development and Benchmarking Platform for Robot Navigation in Highly Dynamic Environments

arXiv: https://arxiv.org/abs/2302.10023 · HTML: https://mlsanity.com/paper/2302.10023/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 33 references that are in the map.
- First posted on arXiv 20 Feb 2023.

## Builds on (most cited first, 17 of 17)

- [Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning](https://mlsanity.com/paper/1809.08835/) (2018)
- [Socially Aware Motion Planning with Deep Reinforcement Learning](https://mlsanity.com/paper/1703.08862/) (2017)
- [Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning](https://mlsanity.com/paper/1805.01956/) (2018)
- [Interactive Gibson Benchmark (iGibson 0.5): A Benchmark for Interactive Navigation in Cluttered Environments](https://mlsanity.com/paper/1910.14442/) (2019)
- [Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning](https://mlsanity.com/paper/1709.10082/) (2017)
- [PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planning](https://mlsanity.com/paper/1710.03937/) (2017)
- [Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey](https://mlsanity.com/paper/2011.13112/) (2020)
- [APPLD: Adaptive Planner Parameter Learning from Demonstration](https://mlsanity.com/paper/2004.00116/) (2020)
- [SEAN: Social Environment for Autonomous Navigation](https://mlsanity.com/paper/2009.04300/) (2020)
- [NavRep: Unsupervised Representations for Reinforcement Learning of Robot Navigation in Dynamic Human Environments](https://mlsanity.com/paper/2012.04406/) (2020)
- [Arena-Rosnav: Towards Deployment of Deep-Reinforcement-Learning-Based Obstacle Avoidance into Conventional Autonomous Navigation Systems](https://mlsanity.com/paper/2104.03616/) (2021)
- [SOCIALGYM: A Framework for Benchmarking Social Robot Navigation](https://mlsanity.com/paper/2109.11011/) (2021)
- [An Extensible Benchmarking Infrastructure for Motion Planning Algorithms](https://mlsanity.com/paper/1412.6673/) (2014)
- [Arena-Bench: A Benchmarking Suite for Obstacle Avoidance Approaches in Highly Dynamic Environments](https://mlsanity.com/paper/2206.05728/) (2022)
- [All-in-One: A DRL-based Control Switch Combining State-of-the-art Navigation Planners](https://mlsanity.com/paper/2109.11636/) (2021)
- [Deep-Reinforcement-Learning-Based Semantic Navigation of Mobile Robots in Dynamic Environments](https://mlsanity.com/paper/2008.00516/) (2020)
- [MRPB 1.0: A Unified Benchmark for the Evaluation of Mobile Robot Local Planning Approaches](https://mlsanity.com/paper/2011.00491/) (2020)

## Built on by (most cited first, 3 of 3)

- [GSON: A Group-based Social Navigation Framework with Large Multimodal Model](https://mlsanity.com/paper/2409.18084/) (2024)
- [Arena 4.0: A Comprehensive ROS2 Development and Benchmarking Platform for Human-centric Navigation Using Generative-Model-based Environment Generation](https://mlsanity.com/paper/2409.12471/) (2024)
- [RUMOR: Reinforcement learning for Understanding a Model of the Real World for Navigation in Dynamic Environments](https://mlsanity.com/paper/2404.16672/) (2024)

## 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.