Inspection Path Planning for Aerial Vehicles via Sampling-based Sequential Optimization

Liping Shi, Golizheh Mehrooz, Rune Hylsberg Jacobsen

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Abstract

Unmanned Aerial Vehicles (UAVs) commonly called 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 using 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.

Original languageEnglish
Title of host publication2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021
PublisherIEEE
Publication date15. Jun 2021
Pages679-687
Article number9476784
ISBN (Electronic)9780738131153
DOIs
Publication statusPublished - 15. Jun 2021
Event2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021 - Athens, Greece
Duration: 15. Jun 202118. Jun 2021

Conference

Conference2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021
Country/TerritoryGreece
CityAthens
Period15/06/202118/06/2021
SeriesProceedings of International Conference on Unmanned Aircraft Systems
ISSN2575-7296

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