Please use this identifier to cite or link to this item:
Title: Autonomous dynamic docking of UAV based on UWB-vision in GPS-denied environment
Authors: Cheng, Cheng
Li, Xiuxian
Xie, Lihua
Li, Li
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Cheng, 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.
Journal: Journal of The Franklin Institute
Abstract: This 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.
ISSN: 0016-0032
DOI: 10.1016/j.jfranklin.2022.03.005
Schools: School of Electrical and Electronic Engineering 
Rights: © 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

Citations 50

Updated on Mar 1, 2024

Web of ScienceTM
Citations 50

Updated on Oct 30, 2023

Page view(s)

Updated on Mar 1, 2024

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.