We study a joint schedule problem that involves flight planning for the drone and transmission scheduling for sensors, such that the maximum amount of data can be collected with a limited individual energy budget for the UAV and the sensors, respectively.
Authors: Runqun Xiong and Feng Shan
Journal: Sensors 2018, 18(9), 2913
We consider an Unmanned Aerial Vehicle (UAV, also known as drone) as an aerial sink to travel along a natural landscape or rural industrial linear infrastructure to collect data from deployed sensors. We study a joint schedule problem that involves flight planning for the drone and transmission scheduling for sensors, such that the maximum amount of data can be collected with a limited individual energy budget for the UAV and the sensors, respectively. On one hand, the flight planning decides the flight speed and flight path based on sensor locations, energy budgets, and the transmission schedule. On the other hand, the transmission schedule decides for each sensor when to deliver data and what transmission power to use based on the energy budgets and flight plan. By observing three import optimality properties, we decouple the joint problem into two subproblems: drone flight planning and sensor transmission scheduling. For the first problem, we propose a dynamic programming algorithm to produce the optimal flight planning. For the second problem, with a flight plan as input, we introduce a novel technique (water-tank), which together with dynamic programming, is the key to achieve an optimal transmission schedule that maximizes data collection. Simulations show that the separately determined flight plan and transmission schedule are near-optimal for the original joint problem.
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
Illustration of a drone flies along a coastline to collect data from deployed sensors. By mainstream open-source or commercial flight controllers, a flight path consists of a sequence of way-points that the drone visits and makes turn at, so they are also called turning points (red solid points). More turning points means more energy consumption of the drone since more flight time and distance to cover, however, it also means closer the drone can fly to sensors to collect data. Fewer turning points consumes less drone energy, but cost sensors to use higher power to transmit data due to the longer distance. The best trade-off with limited drone and sensors energy must be found. (credits: Runqun Xiong and Feng Shan)