Cooperative patrol path planning method for air-ground heterogeneous robot system

被引：0
|
作者：
Hu Z.-F. [1 ,2 ]
Chen Y. [1 ,2 ]
Zheng X.-J. [1 ,2 ]
Wu H.-Y. [1 ,2 ]
机构：
[1] Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education, Wuhan
[2] Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology, Wuhan
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2022年 / 39卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Air-ground collaboration; Ant colony algorithm; Genetic algorithm; Persistent patrol; Road network constraints;
D O I：
10.7641/CTA.2021.00918
中图分类号：
学科分类号：
摘要：
The air-ground heterogeneous robot system consists of drones and unmanned ground vehicles (UGVs). When they cooperate on continuous patrol, using UGVs as mobile charging station for the drones can solve the problem of insufficient drone battery life. The UGVs which are restricted in the road network replenish energy for drones at appropriate locations, this makes the paths of the two vehicles highly coupled and brings challenges to air-ground cooperative path planning. To solve this problem, this paper analyzes the constraints of UAV energy, road network, air-ground convergence time, full coverage of patrol missions, and establishes an air-ground cooperative patrol path planning model with the total distance of the UAV completing all patrol missions as a cost function. This model can be extended to situations where multiple drones cooperate with multiple UGVs. Then, the combination of genetic algorithm and ant colony algorithm is used to optimize the patrol path of drones and the energy supply path of UGVs simultaneously. Simulation experiments show that the proposed method not only can obtain good path planning results, but also has better convergence and execution speed than other algorithms. © 2022, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
引用
收藏
页码：48 / 58
页数：10
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