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蚁群算法

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  • Update : 2017-09-21
  • Size : 40.49mb
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  • Author :毛*****
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Introduction - If you have any usage issues, please Google them yourself
Path planning is one of the key technologies of underwater vehicle intelligent control, whose task is to follow a certain environment in a known obstacle The optimal index searches for a collision free path from the starting point to the target point. Three dimensional space path planning for underwater vehicle using ant colony algorithm Questions were studied in order to ACS Based on the algorithm, a path optimization search algorithm is designed, and the pheromone representation method and path are discussed in detail The principle of point selection, heuristic function design and pheromone updating rules are given. The flow chart of the algorithm is given. The simulation results show that the algorithm is very effective, The algorithm can realize path planning in 3D space conveniently and effectively.
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蚁群算法\CacuFit.asv
蚁群算法\CacuFit.m
蚁群算法\CacuQfz.asv
蚁群算法\CacuQfz.m
蚁群算法\data.asv
蚁群算法\data.m
蚁群算法\data.mat
蚁群算法\data1.m
蚁群算法\information1.mat
蚁群算法\initiation.asv
蚁群算法\main.asv
蚁群算法\main.m
蚁群算法\main1.asv
蚁群算法\main1.m
蚁群算法\path.asv
蚁群算法\path1.asv
蚁群算法\path1.m
蚁群算法\searchpath.asv
蚁群算法\searchpath.m
蚁群算法\z1.mat
蚁群算法\~$附件1 区域高程数据.xlsx
蚁群算法\结果.bmp
蚁群算法\适应度变化.bmp
蚁群算法\附件1 区域高程数据.xlsx
蚁群算法
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