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Scott, Kevon KOcclusion-Aware Sensing and Coverage in Unmanned Aerial Vehicle (UAV) Networks
MS, University of Cincinnati, 2016, Engineering and Applied Science: Computer Engineering
The use of small and miniature Unmanned Aerial Vehicles (UAVs) for remote sensing and surveillance applications has become increasingly popular in the last two decades. Networks of UAVs, capable of providing flexible aerial views over large areas, are playing important roles in today's distributed sensing systems. Since camera sensors are sensitive to occlusions, it is more challenging to deploy UAVs for sensing in geometrically complex environments, such as dense urban areas and mountainous terrains. The intermittent connectivity in a sparse UAV network also makes it challenging to efficiently gather sensed multimedia data. This thesis is composed of two pieces of work. In the first piece of work, a new occlusion-aware UAV coverage technique with the objective of sensing a target area with satisfactory spatial resolution subject to the energy constraints of UAVs is proposed. An occlusion-aware waypoint generation algorithm is first designed to find the best set of waypoints for taking pictures in a target area. The selected waypoints are then assigned to multiple UAVs by solving a vehicle routing problem (VRP), which is formulated to minimize the maximum energy for the UAVs to travel through the waypoints. A genetic algorithm is designed to solve the VRP problem. Evaluation results show that the proposed coverage technique can reduce energy consumption while achieving better coverage than traditional coverage path planning techniques for UAVs. In the second piece of work, a communication scheme is designed to deliver the images sensed by a set of mobile survey UAVs to a static base station through the assistance of a relay UAV. Given the planned routes of the survey UAVs, a set of relay waypoints are found for the relay UAV to meet the survey UAVs and receive the sensed images. An Online Message Relaying technique (OMR) is proposed to schedule the relay UAV to collect images. Without any global collaboration between the relay UAV and the survey UAVs, OMR utilizes a markov decision process (MDP) that determines the best schedules for the relay UAV such that the image acquisition rate could be maximized. Evaluation results show that the proposed relaying technique outperforms traditional relaying techniques, such as the traveling salesman problem (TSP) and the random walk, in terms of end-to-end delay and frame delivery ratio.


Rui Dai, Ph.D. (Committee Chair); Dharma Agrawal, D.Sc. (Committee Member); Carla Purdy, Ph.D. (Committee Member)


Computer Engineering


Unmanned Aerial Vehicle;UAV;Occlusion;FANET;Flying Ad-Hoc Networks;Remote Sensing