Pathfinding algorithm of unmanned aerial vehicle based on deep learning

Haifeng Lin; Chen Chen; Junlin Chen; Guosong Zhu

doi:10.1117/12.2686998

21 July 2023 Pathfinding algorithm of unmanned aerial vehicle based on deep learning

Haifeng Lin, Chen Chen, Junlin Chen, Guosong Zhu

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 127171H (2023) https://doi.org/10.1117/12.2686998
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

Pathfinding algorithm has a decisive impact on unmanned aerial vehicle flight. In practical applications, aerial vehicle is often required to respond to emergencies quickly and plan a new path in time. Therefore, we designed a pathfinding optimization algorithm, combined with the object detection algorithm based on deep learning network, to identify objects that suddenly appear on the original path, timely avoid and re-plan the path. Experiments show that the proposed method can re-plan the new safe path in a short time which satisfies the requirements in response time and path planning.

Citation Download Citation

Haifeng Lin, Chen Chen, Junlin Chen, and Guosong Zhu "Pathfinding algorithm of unmanned aerial vehicle based on deep learning", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 127171H (21 July 2023); https://doi.org/10.1117/12.2686998

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