Open AccessApplication study of UAV path planning based on the balanced search factor artificial bee colony algorithm
Author(s) -
Wei Hao,
Bo Luo,
Zhiyuan Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2083/3/032064
Subject(s) - motion planning , artificial bee colony algorithm , robustness (evolution) , path (computing) , computer science , mathematical optimization , convergence (economics) , population , search algorithm , local search (optimization) , any angle path planning , artificial intelligence , algorithm , mathematics , biology , biochemistry , demography , sociology , robot , economics , gene , programming language , economic growth
In this paper, aiming at the shortcomings of slow convergence speed and weak local search ability of traditional artificial bee colony algorithm in path planning, an artificial bee colony algorithm based on balanced search factor is proposed for UAV path planning. Using a search strategy based on balanced search factor, the depth search is carried out while maintaining a certain population diversity. The global search ability and local development ability are balanced, the average accuracy of path planning is improved, the robustness of path planning is enhanced, and the ability to obtain better path solutions is improved.