Occlusion-Aware Coverage for Efficient Visual Sensing in Unmanned Aerial Vehicle Networks

Abstract

Networks of unmanned aerial vehicles (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. This paper proposes 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. 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 by 16.1% while achieving better coverage than traditional coverage path planning techniques for UAVs.