Arena-Web -- A Web-based Development and Benchmarking Platform for Autonomous Navigation Approaches

TL;DR

Arena-Web is an accessible, web-based platform that simplifies the development, training, and benchmarking of deep reinforcement learning navigation algorithms for robots, making advanced robotics research more accessible to non-experts.

Contribution

This paper introduces Arena-Web, a novel web-based interface that enables easy, code-free development and testing of DRL navigation approaches for various robotic platforms.

Findings

User-friendly web interface for DRL navigation development

Open access platform for benchmarking robotic navigation approaches

Simplifies complex DRL training processes for non-experts

Abstract

In recent years, mobile robot navigation approaches have become increasingly important due to various application areas ranging from healthcare to warehouse logistics. In particular, Deep Reinforcement Learning approaches have gained popularity for robot navigation but are not easily accessible to non-experts and complex to develop. In recent years, efforts have been made to make these sophisticated approaches accessible to a wider audience. In this paper, we present Arena-Web, a web-based development and evaluation suite for developing, training, and testing DRL-based navigation planners for various robotic platforms and scenarios. The interface is designed to be intuitive and engaging to appeal to non-experts and make the technology accessible to a wider audience. With Arena-Web and its interface, training and developing Deep Reinforcement Learning agents is simplified and made easy without a single line of code. The web-app is free to use and openly available under the link stated in the supplementary materials.