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29 November 2023 Research on optimization of UAV patrol inspection path planning for the intelligent warehouse
Yi Ding, Lisha Zhang, Ge Song
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Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 1293711 (2023) https://doi.org/10.1117/12.3013645
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore
Abstract
The Unmanned Aerial Vehicle (UAV) inspection path planning for intelligent warehouse is a typical indoor path planning technology. Through the UAV intelligent inspection of each work area in the intelligent warehouse and workshop, we can solve some issues occurred in the work area timely. In order to solve the problem of path planning efficiently, an improved hybrid optimization algorithm is proposed to minimize the inspection path, which combines intelligent optimization algorithms of particle swarm optimization and genetic algorithm. By optimizing the structure of the genetic algorithm and finding the optimal parameter combination, it is easier to converge to the shortest path for the intelligent warehouse. Simulation results show that, compared with the traditional algorithms, the convergence ability of the optimized hybrid algorithm has been greatly improved, which has also been verified.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yi Ding, Lisha Zhang, and Ge Song "Research on optimization of UAV patrol inspection path planning for the intelligent warehouse", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 1293711 (29 November 2023); https://doi.org/10.1117/12.3013645
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KEYWORDS
Particle swarm optimization
Inspection
Unmanned aerial vehicles
Genetic algorithms
Evolutionary algorithms
Mathematical optimization
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