Optimal path planning for UAV based inspection system of large-scale photovoltaic farm

Small scale quad-rotor unmanned aerial vehicle (UAV) has attracted much attention in recent years and has been widely adopted in many civil applications, e.g. inspection of critical infrastructure spanning over a large geographical area. In a typical UAV based inspection system for large-scale photovoltaic farm, it is required to control the mounted gimbal camera taking pictures of all the PV modules and eventually accurately identify the ones with defects through efficient image processing techniques. Given a series of waypoints without an effective path generation algorithm, the image acquisition can be not satisfactory and even miss some areas that should be inspected. In this paper, a Bezier curve and particle swarm optimization (PSO) joint approach is presented to address the UAV path planning challenge. The path generation process fully takes flight attitude, gimbal limitation and path length into consideration with the aim to improve the efficiency and the reliability of the inspection system. The performance of the proposed solution is assessed through a set of simulation experiments and the numerical result demonstrates the effectiveness of the proposed optimal path planning solution.