Aerial Data Collection with Coordinated UAV and Truck Route Planning in Wireless Sensor Network

Unmanned aerial vehicle (UAV) is a promising way to collect data generated by wireless sensor networks, nevertheless, the battery capacity of the UAV restricts its application on many occasions, e.g., the network deployed in the wild. In this paper, we propose a coordinated route planning scheme to deal with the energy issue of the UAV, where a truck carrying backup batteries moves together with the UAV as a "mobile recharging station". Our optimization task is to minimize the total mission time for collecting data from all the sensor nodes. We develop an efficient clustering algorithm to divide the entire mission area into multiple subregions in a load-balanced way to minimize the number of movements of the UAV, and formulate the trajectory planning task as a coordinated traveling salesman problem which is heuristically solved by a three-step route planning algorithm. Numerical results show that our proposed scheme provides an effective and cost-efficient way for the data collection of wireless sensor networks in practical application scenarios.