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A Multi-robot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-inspired Neural Network

Chen, Bo; Zhang, Hui; Zhang, Fangfang; Liu, Yanhong; Tan, Cheng; Yu, Hongnian; Wang, Yaonan


Bo Chen

Hui Zhang

Fangfang Zhang

Yanhong Liu

Cheng Tan

Yaonan Wang


There are many constraints for a multi-robot system to perform a region coverage search task in an unknown environment. To address this, we propose a novel multi-robot distributed collaborative region coverage search algorithm based on Glasius bio-inspired neural network (GBNN). Firstly, we develop an environmental information updating model to represent the dynamic search environment. This model converts the environmental information detected by the robot into dynamic neural activity landscape of GBNN. Secondly, we introduce the distributed model predictive control method in search path planning to improve search efficiency. In addition, we propose a distributed collaborative decision-making mechanism among the robots to produce several dynamic search sub-teams. Within each sub-team, collaborative decisions are made among the robot members to optimize the solution and obtain the next movement path of each robot. Finally, we conduct experiments in three aspects to verify the effectiveness of the proposed method. Compared with three algorithms in this field, the experimental results demonstrate that the proposed algorithm exhibits good performance in a multi-robot region coverage search task.

Journal Article Type Article
Acceptance Date Oct 28, 2022
Online Publication Date Nov 1, 2022
Publication Date 2023-09
Deposit Date Dec 16, 2022
Journal IEEE Transactions on Cognitive and Developmental Systems
Print ISSN 2379-8920
Electronic ISSN 2379-8939
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 15
Issue 3
Pages 1449-1462
Keywords Multi-robot system, region coverage search, Glasius bio-inspired neural network , distributed collaborative decision-making mechanism, search sub-team
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