Double Heuristic Optimization Based on Hierarchical Partitioning for Coverage Path Planning of Robot Mowers

被引：0
|
作者：
Wang, Jingyu [1 ]
Chen, Junfeng [1 ,2 ,3 ]
Cheng, Shi [4 ]
Xie, Yingjuan [1 ,2 ,3 ]
机构：
[1] Hohai Univ, Coll IOT Engn, Changzhou, Peoples R China
[2] Hohai Univ, Jiangsu Key Lab Power Transmiss & Distribut Equip, Changzhou, Peoples R China
[3] Changzhou Key Lab Sensor Networks & Environm Sens, Changzhou, Peoples R China
[4] Shaanxi Normal Univ, Sch Comp Sci, Xian, Peoples R China
来源：
PROCEEDINGS OF 2016 12TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2016年
基金：
中国国家自然科学基金;
关键词：
robot mowers; coverage path planning; hierarchical partitioning; ant colony optimization; tabu search;
D O I：
10.1109/CIS.2016.50
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Coverage path planning is one of the important issues for robot mowers, which brings great convenience to our life. In this paper, hierarchical partitioning strategy is employed to fulfill robot's environment modeling and the double heuristic optimization algorithms have been adopted to plan optimal coverage paths. Ant Colony Optimization (ACO) is used for global path planning in the upper layer, and Tabu Search (TS) is used for local coverage planning in the lower layer. Finally, simulation experiments are carried out and the results show the proposed method obtains satisfactory coverage path planning.
引用
收藏
页码：186 / 189
页数：4
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