The research on multi-robot collaborative search based on bio-inspired neural networks in 3D unknown environments is of great value and significance, but robots tend to fall into local optimum in the late search period. This article proposes a multi-robot collaborative search algorithm based on the GBNN model for the problem of multi-robot collaborative coverage search in a 3D unknown environment. When the robot is in a local optimal state, we use a guiding target point to help the robot jump out of the local optimal state and reach the unsearched area. Finally, simulation experiments were conducted to verify the effectiveness of the proposed algorithm. Based on random starting points, complete coverage can be achieved.
An Improved Multi-robot Coverage Method in 3D Unknown Environment Based on GBNN
Lect. Notes Electrical Eng.
Chinese Intelligent Automation Conference ; 2023 ; Nanjing, China October 02, 2023 - October 05, 2023
Proceedings of 2023 Chinese Intelligent Automation Conference ; Chapter : 47 ; 476-483
2023-09-23
8 pages
Article/Chapter (Book)
Electronic Resource
English
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