3D Trajectory Optimization for Multimission UAVs in Smart City Scenarios

计算机科学 弹道 轨迹优化 实时计算 天文 物理
作者
Nicola Roberto Zema,Enrico Natalizio,Luigi Di Puglia Pugliese,Francesca Guerriero
出处
期刊:IEEE Transactions on Mobile Computing [IEEE Computer Society]
卷期号:23 (1): 1-11 被引量:6
标识
DOI:10.1109/tmc.2022.3215705
摘要

There is a definite possibility that, in a recent future, Unmanned Aerial Vehicles (UAVs) will form the backbone of any smart city in terms of automation and networking. One approach to extend the UAVs' resources spectrum is to provide a mean for them to opportunistically recharge and connect to otherwise unreachable networks: provide Training and Recharge Areas (TRAs). In these dedicated areas, the UAVs could dock to Energy and Data Dispensers (EDD) devices to resupply their batteries and exploit a high-speed connection. To autonomously move through the smart city while accomplishing a set of given tasks but, at the same time, consider visiting the EDDs, is part of a tridimensional trajectory planning problem that needs to be addressed. In this paper, we formally define the combinatorial optimization problem representing the trajectory planning. We consider the case in which more than one UAV can be connected with the same EDD at the same time, by properly addressing the assignment of the bandwidth. Through simulative investigation, realistic values for the solution of the optimization problem are found. The behavior of the proposed model is compared with an "online" approach that does not require the same resources and knowledge and whose evaluation and comparison with the "offline" approach are performed through network simulation.
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