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Issue title: Artificial Intelligence and Advanced Manufacturing (AIAM 2020)
Guest editors: Shengzong Zhou
Article type: Research Article
Authors: Dai, Xuefenga; * | Wang, Jiazhia | Li, Dahuia | Wang, Yanchunb
Affiliations: [a] School of Computer and Control Engineering, Qiqihar University, Heilongjiang, China | [b] School of Communication and Electronics Engineering, Qiqihar University, Heilongjiang, China
Correspondence: [*] Corresponding author. Xuefeng Dai, School of Computer and Control Engineering, Qiqihar University, Heilongjiang, China. E-mail: [email protected].
Abstract: Multi-robot systems have many potential applications; however, the available results for coordination were based on qualitative information. Fuzzy logic reasoning has a feature of human being thinking, so a novel coordinated algorithm is proposed. The algorithm utilizes sharing sensing information of rooms and semantic robots to coordinating robots in a structured environment exploration. The approach divides all teammate robots into two classes according to robot exploration performance, and divides rooms into large, medium and small ones according to estimations of the individual areas. On the purpose of minimizing exploration time of the system, the reasoning coordination assigns large room to good performance robot, and vice versa. A parameter update law is introduced for fuzzy membership functions. Finally, the results are validated by computer simulations for a structured environment.
Keywords: Multi-robot systems, fuzzy reasoning, intelligent coordination, task assignments
DOI: 10.3233/JIFS-189682
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 3, pp. 4203-4210, 2021
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