Research Article
Cost Function Minimization-Based Joint UAV Path Planning and Charging Station Deployment (Workshop)
@INPROCEEDINGS{10.1007/978-3-030-41117-6_31, author={Tao Wei and Rong Chai and Qianbin Chen}, title={Cost Function Minimization-Based Joint UAV Path Planning and Charging Station Deployment (Workshop)}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part II}, proceedings_a={CHINACOM PART 2}, year={2020}, month={2}, keywords={UAV Path planning Charging station deployment Cost function}, doi={10.1007/978-3-030-41117-6_31} }- Tao Wei
Rong Chai
Qianbin Chen
Year: 2020
Cost Function Minimization-Based Joint UAV Path Planning and Charging Station Deployment (Workshop)
CHINACOM PART 2
Springer
DOI: 10.1007/978-3-030-41117-6_31
Abstract
The rapid development of automatic control, wireless communication and intelligent information processing promotes the prosperity of unmanned aerial vehicles (UAVs) technologies. In some applications, UAVs are required to fly from given source places to certain destinations for task execution, a reasonable path planning and charging stations (CSs) strategy can be designed to achieve the performance enhancement of task execution of the UAVs. In this paper, we consider joint UAV path planning and CS deployment problem. Stressing the importance of the total time of the UAVs to perform tasks and the cost of deploying and maintaining CSs, we formulate the joint path planning and CS deployment problem as a cost function minimization problem. Since the formulated optimization problem is an NP-hard problem which cannot be solved easily, we propose a heuristic algorithm which successively solves two subproblems, i.e, path planning subproblem and destination path selection subproblem by applying the A* algorithm, K-shortest path algorithm and genetic algorithm (GA), respectively. Simulation results validate the effectiveness of the proposed algorithm.
