文件名称:蚁群算法
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路径规划是水下潜器智能控制的关键技术之一,其任务是在已知障碍物的环境中按照某一
最优指标寻找一条从起始点到目标点的无碰路径。使用蚁群算法对水下潜器三维空间路径规划问
题进行了研究,以
ACS
算法为基础设计了路径优化搜索算法,详细讨论了信息素表示方法、路径
点选取原则、启发式函数设计和信息素更新规则,给出了算法的具体流程,仿真实验结果表明,
该算法能够方便有效的实现三维空间中的路径规划。(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.)
最优指标寻找一条从起始点到目标点的无碰路径。使用蚁群算法对水下潜器三维空间路径规划问
题进行了研究,以
ACS
算法为基础设计了路径优化搜索算法,详细讨论了信息素表示方法、路径
点选取原则、启发式函数设计和信息素更新规则,给出了算法的具体流程,仿真实验结果表明,
该算法能够方便有效的实现三维空间中的路径规划。(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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下载文件列表
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\~$附件1 区域高程数据.xlsx
蚁群算法\结果.bmp
蚁群算法\适应度变化.bmp
蚁群算法\附件1 区域高程数据.xlsx
蚁群算法
蚁群算法\CacuFit.m
蚁群算法\CacuQfz.asv
蚁群算法\CacuQfz.m
蚁群算法\data.asv
蚁群算法\data.m
蚁群算法\data.mat
蚁群算法\data1.m
蚁群算法\information1.mat
蚁群算法\initiation.asv
蚁群算法\main.asv
蚁群算法\main.m
蚁群算法\main1.asv
蚁群算法\main1.m
蚁群算法\path.asv
蚁群算法\path1.asv
蚁群算法\path1.m
蚁群算法\searchpath.asv
蚁群算法\searchpath.m
蚁群算法\z1.mat
蚁群算法\~$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