On benchmarking of frontier-based multi-robot exploration strategies

J. Faigl, Miroslav Kulich
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引用次数: 40

Abstract

This paper tackles an evaluation and comparison of frontier-based exploration strategies to create a grid map of unknown environment by a team of autonomous mobile robots. A strategy is considered as a set of procedures to determine promising goal candidates, allocate them to the robots, and select the next navigational goal for each robot. A mobile robot is a complex system with many components that affect the mission performance and a comparison of different strategies in real experiments can be performed only for a particular system setup and with only partial controllability of important parameters. Therefore, the reproducibility and repeatability of such a comparison are not satisfied. In this paper, we propose a methodology for evaluating exploration strategies and provide a benchmark for a comparison of frontier-based approaches in a well-defined evaluation environment. The proposed methodology is demonstrated on a comparison of five state-of-the-art task-allocation strategies in multi-robot exploration.
基于边界的多机器人探索策略的标杆测试
本文对一组自主移动机器人基于边界的探索策略进行了评估和比较,以创建未知环境的网格地图。策略被认为是一组确定有希望的目标候选者,将它们分配给机器人,并为每个机器人选择下一个导航目标的过程。移动机器人是一个复杂的系统,有许多影响任务性能的部件,在实际实验中,不同策略的比较只能针对特定的系统设置进行,并且重要参数只能部分可控。因此,这种比较的再现性和可重复性并不令人满意。在本文中,我们提出了一种评估勘探策略的方法,并为在定义良好的评估环境中比较基于边界的方法提供了基准。通过对多机器人探索中五种最先进的任务分配策略的比较,证明了所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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