Spatial Path–Energy Optimization for UAV Operation in Arial–Ground Networking

Abstract

Small unmanned aerial vehicles (UAVs) are emerging as transformative platforms for different geospatial applications. In these scenarios, multidestination path planning becomes critical due to their energy limitation. However, how to tactically operate a UAV with its limited energy source considering per-destination tasking in a network is not fully answered. An optimization framework is developed in this paper by casting the formulation as a classical traveling salesman problem with neighborhoods (TSPN). The authors introduce a packet-loss function and propose optimizing the total cost with the hovering-induced cost as a regularization term. The framework yields two upper-bound schemes and one regularized solution by considering the hovering-induced energy, the dynamically minimized path-energy (DM-PE) solution. The simulation results, based on both small and large-scale networks, verify that the DM-PE scheme warrants the most minimal path-energy cost among the three solutions.