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dc.contributor.authorCheng, Chengen_US
dc.contributor.authorLi, Xiuxianen_US
dc.contributor.authorXie, Lihuaen_US
dc.contributor.authorLi, Lien_US
dc.identifier.citationCheng, C., Li, X., Xie, L. & Li, L. (2022). Autonomous dynamic docking of UAV based on UWB-vision in GPS-denied environment. Journal of The Franklin Institute, 359(7), 2788-2809.
dc.description.abstractThis paper studies the autonomous docking between an Unmanned Aerial Vehicle (UAV) and a Mobile Platform (MP) based on UWB and vision sensors. To solve this problem, an integrated estimation and control scheme is proposed, which is divided into three phases: hovering, approaching and landing. In the hovering phase, the velocity of the MP and relative position between the MP and UAV are estimated by using geometric tools and Cayley-Menger determinant based on ultra-wideband distance measurements; in the approaching phase, a recursive least squares optimization algorithm with a forgetting factor is proposed, which uses distance, displacement and MP's velocity to estimate the relative position between the UAV and MP. With the estimated relative position, UAV can approach MP until reaching a distance such that MP is within the field of view of UAV; in the landing phase, the UWB measurement value and visual perception attitude are integrated with the UAV on-board navigation sensor of the UAV to perform the precision landing. Simulation and experiment results verify the effectiveness and feasibility of the proposed integrated navigation scheme.en_US
dc.relation.ispartofJournal of The Franklin Instituteen_US
dc.rights© 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleAutonomous dynamic docking of UAV based on UWB-vision in GPS-denied environmenten_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.subject.keywordsPrecision Landingen_US
dc.description.acknowledgementThis research was supported by the Shanghai Municipal Commission of Science and Technology No. 19511132100, 19511132101, the Shanghai Municipal Science and Technology Major Project, No. 2021SHZDZX0100, the National Natural Science Foundation of China under Grant 62003243, National Key R&D Program of China, No. 2018YFE0105000, 2018YFB1305304, and the Basic Science Centre Program by National Natural Science Foundation of China under grant 62088101.en_US
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