Journal of Dalian Maritime University >
2018 , Vol. 44 >Issue 4: 35 - 42
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2018.04.006
Automatic collision avoidance algorithm for unmanned surface vehicle based on improved bacterial foraging optimization
Received date: 2018-05-02
Revised date: 2018-08-03
Online published: 2018-08-03
To solve the collision avoidance planning problem of unmanned surface vehicle（USV）, an automatic collision avoidance algorithm was designed based on improved bacterial foraging optimization（BFO）. Aiming at the shortcomings of slow convergence speed, low optimization precision and low stability resulted from basic BFO, an adaptive diminishing fractal dimension chemotactic step length was designed to replace the fixed step length in order to realize the adaptive adjustment of step length. The optimal search method was put forward to solve the defects of ineffective swimming and repeated swimming in the basic BFO algorithm. An adaptive migration probability was designed instead of fixed migration probability to solve the problem of elite individual loss caused by basic BFO algorithm. The function test simulation shows that the improved BFO algorithm has better convergence speed, better optimization precision and better stability. The improved algorithm was applied into USV collision avoidance simulation, and results show that the improved algorithm can quickly and safely realize the autonomous collision avoidance of UAV under dynamic obstacles.
ZENG Xiao-long , MAO Yun-sheng , SONG Li-fei , DONG Zao-peng , BAO Tao . Automatic collision avoidance algorithm for unmanned surface vehicle based on improved bacterial foraging optimization[J]. Journal of Dalian Maritime University, 2018 , 44(4) : 35 -42 . DOI: 10.16411/j.cnki.issn1006-7736.2018.04.006
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