Abstract
This paper proposes a study on the autonomous driving of the boarding junction/departure mission, which is one of the representative facilities of an airport. To achieve this goal, route planning and moving technology are necessary to enable quick movement to the destination point. In order to achieve the goal, we propose a technology that accurately recognizes the target point of the aircraft door to be docked. To this end, we apply a technology that can recognize the aircraft door more accurately and quickly, using the YOLO algorithm, and minimize the difference in input image data according to various environments and times. Finally, we introduce a technique for linking the calculated target position with the controller.
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Acknowledgements
This study was supported by Korea Evaluation Institute of Industral Technology (KEIT) grant funded by the Korea government(MOTIE) (No.20023455, Dvelopment of Cooperate Mappint, Environmnet Recogntion and Autonomous Driving Techonology for Multi Mobile Robots Operating in Large-scale Indoor Workspace) and conducted with research support from Incheon International Airport Corporation.
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Weon, I., Park, B., Kim, HJ., Park, JH. (2024). Development of Autonomous Driving for Passenger Boarding Bridge (PBB) Through Aircraft Door Detection Based on YOLO Object Detection Algorithm. In: Lee, SG., An, J., Chong, N.Y., Strand, M., Kim, J.H. (eds) Intelligent Autonomous Systems 18. IAS 2023. Lecture Notes in Networks and Systems, vol 794. Springer, Cham. https://doi.org/10.1007/978-3-031-44981-9_17
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DOI: https://doi.org/10.1007/978-3-031-44981-9_17
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