Occlusion-aware UAV Path Planning for Reconnaissance and Surveillance in Complex Environments

This paper concerns the reconnaissance and surveillance problem for multi-rotor aerial drones or unmanned aerial vehicles (UAVs) flying over geometrically complex environments, such as mountainous terrains and urban regions. In contrast to the existing literature, our approach takes both UAV kinematics constraints and camera sensing constraints into consideration. We present a two-stage strategy to solve this UAV surveillance problem with the given terrain information. In the first stage, the challenge is to find a set of camera locations called the vantage waypoint set to provide full coverage of the area of interest, which can be viewed as a 3D Art Gallery Problem using drones as the observers. In the second stage, one or several UAVs are determined to conduct the full coverage reconnaissance and surveillance duty along individual routes respecting their kinematic constraints in the optimization criterion (the shortest time possible). This variant of the combinatorial traveling salesman problem is solved by introducing unsupervised learning and Bézier curves. The reported results support the feasibility of the proposed solution.