基于改进蚁群算法的地面机器人三维路径规划

2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) Pub Date : 2018-10-01 DOI:10.1109/CYBERC.2018.00030

Lanfei Wang, Jiangming Kan, Jun Guo, Chao Wang

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引用次数: 3

摘要

路径规划是三维环境下移动机器人导航控制的重要组成部分。针对三维路径规划中容易陷入局部最优、搜索时间长等问题，提出了一种改进的蚁群算法。我们重新设计了信息素更新和启发式功能。为了解决搜索时间问题，设计了新的搜索模式。我们使用了多个3D地形进行实验，并在每个地形中设置了不同的起点和终点。将改进蚁群算法与传统蚁群算法的结果进行比较，改进蚁群算法可将最短路径长度平均缩短8.164%。

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Improved Ant Colony Optimization for Ground Robot 3D Path Planning

Path planning is an important part in the navigation control of mobile robot in a 3D environment. We proposed an improved ant colony algorithm to address the problems of falling into local optimum easily and long search time in 3D path planning. We redesigned pheromone update and heuristic function. New search mode is designed to solve the problem of searching time. We used a number of 3D terrains to carry out experiments, and set different starting and end points in each terrain. By comparing the results of improved ant colony algorithm and traditional ant colony algorithm, the improved one can reduce the shortest path length by an average of 8.164%.

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2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

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