Improved Ant Colony Optimization for Ground Robot 3D Path Planning

被引：6
|
作者：
Wang, Lanfei [1 ]
Kan, Jiangming [2 ]
Guo, Jun [1 ]
Wang, Chao [2 ]
机构：
[1] Beijing Univ Posts & Telecommun, Informat & Commun, Beijing, Peoples R China
[2] Beijing Forestry Univ, Engn Inst, Beijing, Peoples R China
来源：
2018 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC 2018) | 2018年
关键词：
Ground robot; path planning; ant colony optimization; 3D space;
D O I：
10.1109/CyberC.2018.00030
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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 robot 3D path planning. We improved pheromone update and designed 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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页码：106 / +
页数：7
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