关于多机器人任务分配的系统性文献综述

IF 23.8 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2024-10-14 DOI:10.1145/3700591

Athira K A, Divya Udayan J, Umashankar Subramaniam

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引用次数: 0

摘要

多机器人系统正受到越来越多的关注，也是机器人学的重要研究领域之一。目前正在研究多个机器人之间的协调以及如何将不同任务分配给不同的系统代理。本系统文献综述（SLR）的目的是深入探讨多机器人任务分配（MRTA）问题的最新进展，强调任务分配的可行方法。在本研究中，我们从 5 个不同的数据库中收集了有关 MRTA 的科学论文。我们概述了任务分配算法的不同方法，根据方法进行了分类，并强调了最新进展。此外，我们还讨论了不确定性在任务分配中的作用以及任务分配中使用的典型协调技术，以找出文献中的空白并提出最有前途的方法。

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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A Systematic Literature Review on Multi-Robot Task Allocation

Muti-Robot system is gaining attention and is one of the critical areas of research when it comes to robotics. Coordination among multiple robots and how different tasks are allocated to different system agents are being studied. The objective of this Systematic Literature Review (SLR) is to provide insights on the recent advancement in Multi Robot Task Allocation(MRTA) problems emphasizing promising approaches for task allocation. In this study, we collected scientific papers from 5 different databases for MRTA. We outline the different approaches for task allocation algorithms, classifying them according to the methods, and emphasizing recent advances. In addition, we discuss the function of uncertainty in task allocation and typical coordination techniques utilized in task allocation to identify gaps in the literature and suggest the most promising ones.

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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.