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

Liping Shi, Golizheh Mehrooz, Rune Hylsberg Jacobsen

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Abstrakt

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.

OriginalsprogEngelsk
Titel2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021
ForlagIEEE
Publikationsdato15. jun. 2021
Sider679-687
Artikelnummer9476784
ISBN (Elektronisk)9780738131153
DOI
StatusUdgivet - 15. jun. 2021
Begivenhed2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021 - Athens, Grækenland
Varighed: 15. jun. 202118. jun. 2021

Konference

Konference2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021
Land/OmrådeGrækenland
ByAthens
Periode15/06/202118/06/2021
NavnProceedings of International Conference on Unmanned Aircraft Systems
ISSN2575-7296

Bibliografisk note

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation project Drones4Safety under grant agreement No 861111 and the Innovation Fund Denmark project Drones4Energy with project number J. nr. 8057-00038A. We would like to thank Chiara Casarotti and Martina Mandirola from Eucentre for support with insights and data for the bridge inspection use case.

Publisher Copyright:
© 2021 IEEE.

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