IEEE Transactions on Mobile Computing | 2021

Multi-UAV Cooperative Trajectory for Servicing Dynamic Demands and Charging Battery

 
 
 
 

Abstract


Unmanned Aerial Vehicle (UAV) technology is a promising solution for providing high-quality mobile services (e.g., edge computing, fast Internet connection, and local caching) to ground users, where a UAV with limited service coverage travels among multiple geographical user locations (e.g., hotspots) for servicing their demands locally. How to dynamically determine a UAV swarm’s cooperative path planning to best meet many users’ spatio-temporally distributed demands is an important question but is unaddressed in the literature. To our best knowledge, this paper is the first to design and analyze cooperative path planning algorithms of a large UAV swarm for optimally servicing many spatial locations, where ground users’ demands are released dynamically in the long time horizon. Regarding a single UAV’s path planning design, we manage to substantially simplify the traditional dynamic program and propose an optimal algorithm of low computation complexity, which is only polynomial with respect to both the numbers of spatial locations and user demands. After coordinating a large number K of UAVs, this simplified dynamic optimization problem becomes intractable and we alternatively present a fast iterative cooperation algorithm with provable approximation ratio 1− (1− 1 K ) K in the worst case, which is proved to obviously outperform the traditional approach of partitioning UAVs to serve different location clusters separately. To relax UAVs’ battery capacity limit for sustainable service provisioning, we further allow UAVs to travel to charging stations in the mean time and thus jointly design UAVs’ K. Wang, X. Zhang and J. Tie are with the College of Computer Science, South-Central University for Nationalities, Wuhan, China. (E-mails: [email protected], [email protected], [email protected]). K. Wang is also with Department of Information Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China. L. Duan is with Engineering Systems and Design, Singapore University of Technology and Design, Singapore 487372. (E-mail: lingjie [email protected]). A preliminary version of this paper appeared in the Proceedings of IEEE Global Communications Conference 2020 [1]. ar X iv :1 80 5. 08 35 7v 5 [ cs .N I] 3 1 A ug 2 02 1 path planning over users’ locations and charging stations. Despite of the problem difficulty, for the optimal solution, we successfully transform the problem to an integer linear program by creating novel directed acyclic graph of the UAV-state transition diagram, and propose an iterative algorithm with constant approximation ratio. Finally, we validate the theoretical results by extensive simulations.

Volume None
Pages None
DOI 10.1109/tmc.2021.3110299
Language English
Journal IEEE Transactions on Mobile Computing

Full Text