A Survey on Swarm Robotics for Area Coverage Problem

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Algorithms Pub Date : 2023-12-20 DOI:10.3390/a17010003
Dena Kadhim Muhsen, Ahmed T. Sadiq, Firas Abdulrazzaq Raheem
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引用次数: 0

Abstract

The area coverage problem solution is one of the vital research areas which can benefit from swarm robotics. The greatest challenge to the swarm robotics system is to complete the task of covering an area effectively. Many domains where area coverage is essential include exploration, surveillance, mapping, foraging, and several other applications. This paper introduces a survey of swarm robotics in area coverage research papers from 2015 to 2022 regarding the algorithms and methods used, hardware, and applications in this domain. Different types of algorithms and hardware were dealt with and analysed; according to the analysis, the characteristics and advantages of each of them were identified, and we determined their suitability for different applications in covering the area for many goals. This study demonstrates that naturally inspired algorithms have the most significant role in swarm robotics for area coverage compared to other techniques. In addition, modern hardware has more capabilities suitable for supporting swarm robotics to cover an area, even if the environment is complex and contains static or dynamic obstacles.
针对区域覆盖问题的蜂群机器人技术概览
区域覆盖问题的解决方案是可以从蜂群机器人技术中受益的重要研究领域之一。蜂群机器人系统面临的最大挑战是完成有效覆盖区域的任务。许多领域都需要区域覆盖,包括勘探、监控、测绘、觅食和其他一些应用。本文介绍了 2015 年至 2022 年蜂群机器人在区域覆盖方面的研究论文调查,涉及该领域使用的算法和方法、硬件和应用。本文对不同类型的算法和硬件进行了处理和分析;根据分析结果,确定了每种算法和硬件的特点和优势,并确定了它们在不同应用中对多种目标区域覆盖的适用性。这项研究表明,与其他技术相比,自然启发算法在蜂群机器人技术的区域覆盖中发挥着最重要的作用。此外,即使环境复杂,包含静态或动态障碍物,现代硬件也有更多适合支持蜂群机器人覆盖区域的功能。
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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来源期刊
Algorithms
Algorithms Mathematics-Numerical Analysis
CiteScore
4.10
自引率
4.30%
发文量
394
审稿时长
11 weeks
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