Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

Lu Cao; Qiwei Chen

doi:10.1117/12.2285623

8 March 2018 Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

Lu Cao, Qiwei Chen

Proceedings Volume 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 106111G (2018) https://doi.org/10.1117/12.2285623
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

Abstract

Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.

Citation Download Citation

Lu Cao and Qiwei Chen "Cooperative path planning for multi-USV based on improved artificial bee colony algorithm", Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 106111G (8 March 2018); https://doi.org/10.1117/12.2285623

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