Shi, Liping (Aarhus University), Mehrooz, Golizheh (University of Southern Denmark), Jacobsen, Rune (Aarhus University)

Inspection Path Planning for Aerial Vehicles Via Sampling-Based Sequential Optimization

Scheduled for presentation during the Regular Session "Path Planning IV" (ThB3), Thursday, June 17, 2021, 14:20−14:40, Edessa

2021 International Conference on Unmanned Aircraft Systems (ICUAS), June 15-18, 2021, Athens, Greece

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

Unmanned Aerial Vehicles (UAVs) commonly named drones are gaining interest for infrastructure inspection due to their ability to automize and monitor large areas more securely at a lower cost. Autonomous inspection and path planning are essential capabilities for the drone's autonomous flight. In this paper, we propose a novel inspection path planning method for achieving a complete and efficient inspection via drones. A point cloud generated from a 3D mapping service is used to represent complex inspection targets and provided as the input of the path planning method. The method is designed as a sampling-based sequential optimization to calculate and optimize an inspection path while considering the limitation of the sensors, inspection efficiency, and safety requirements of the drones. The proposed method is evaluated for both the use case of bridge inspection and power pylon inspection. A comparison between the proposed path search algorithm and TSP solver is made. Furthermore, the scalability of the method is assessed with different sizes of the inspection problem.