Dynamic collision avoidance method for unmanned surface vehicle based on improved particle swarm optimization

  • FAN Yun-sheng ,
  • ZHENG Kun-peng ,
  • ZHAO Yong-sheng
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  • (Marine Electrical Engineering College, Dalian Maritime University, Dalian 116026,China)

Received date: 2019-08-05

  Revised date: 2019-11-02

  Online published: 2019-11-02

Abstract

A dynamic collision avoidance method based on the improved particle swarm optimization (PSO) algorithm was proposed for the dynamic collision avoidance problem of “LanXin” unmanned surface vehicle. Firstly, as the different aspect ratio of obstacle contour, the obstacle was expanded into a circle and an ellipse to acquire the collision avoidance model by using the principle of velocity obstacle. At the same time, the international rules of collision avoidance were added in the process of collision avoidance. Secondly, the PSO algorithm was improved adaptively, so that the calculation of collision avoidance strategy can quickly converge to the optimal solution, and improved the convergence speed and accuracy of algorithm for satisfying the rapid requirements of the collision avoidance algorithm. Finally, a virtual visual simulation platform was built to simulate the marine environment in navigation,and taking the “LanXin” unmanned surface vehicle as the simulated object to verify the efficiency of the proposed avoidance algorithms. The simulation results show the feasibility and effectiveness of the proposed collision avoidance method, which provide a feasible and effective solution for the autonomous dynamic collision avoidance of unmanned surface vehicle.

Cite this article

FAN Yun-sheng , ZHENG Kun-peng , ZHAO Yong-sheng . Dynamic collision avoidance method for unmanned surface vehicle based on improved particle swarm optimization[J]. Journal of Dalian Maritime University, 2020 , 46(1) : 1 -9 . DOI: 10.16411/j.cnki.issn1006-7736.2020.01.001

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