Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection

In built infrastructure monitoring, an efficient path planning algorithm is essential for robotic inspection of large surfaces using computer vision. In this work, we first formulate the inspection path planning problem as an extended travelling salesman problem (TSP) in which both the coverage and...

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Veröffentlicht in:Automation in construction 2017-09, Vol.81, p.25-33
Hauptverfasser: Phung, Manh Duong, Quach, Cong Hoang, Dinh, Tran Hiep, Ha, Quang
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Sprache:eng
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Zusammenfassung:In built infrastructure monitoring, an efficient path planning algorithm is essential for robotic inspection of large surfaces using computer vision. In this work, we first formulate the inspection path planning problem as an extended travelling salesman problem (TSP) in which both the coverage and obstacle avoidance were taken into account. An enhanced discrete particle swarm optimization (DPSO) algorithm is then proposed to solve the TSP, with performance improvement by using deterministic initialization, random mutation, and edge exchange. Finally, we take advantage of parallel computing to implement the DPSO in a GPU-based framework so that the computation time can be significantly reduced while keeping the hardware requirement unchanged. To show the effectiveness of the proposed algorithm, experimental results are included for datasets obtained from UAV inspection of an office building and a bridge. •Inspection path planning as travelling salesman problem•Discrete PSO, deterministic initialization, random mutation, edge exchange•GPU-based parallel computation•UAV inspection for a building and a bridge
ISSN:0926-5805
1872-7891
DOI:10.1016/j.autcon.2017.04.013