A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments

This study designs a navigation and landing scheme for an unmanned aerial vehicle (UAV) to autonomously land on an arbitrarily moving unmanned ground vehicle (UGV) in GPS-denied environments based on vision, ultra-wideband (UWB) and system information. In the approaching phase, an effective multi-in...

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Main Authors: Cheng, Cheng, Li, Xiuxian, Xie, Lihua, Li, Li
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/174004
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1740042024-03-15T15:39:55Z A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments Cheng, Cheng Li, Xiuxian Xie, Lihua Li, Li School of Electrical and Electronic Engineering Engineering Navigation Sensor fusion This study designs a navigation and landing scheme for an unmanned aerial vehicle (UAV) to autonomously land on an arbitrarily moving unmanned ground vehicle (UGV) in GPS-denied environments based on vision, ultra-wideband (UWB) and system information. In the approaching phase, an effective multi-innovation forgetting gradient (MIFG) algorithm is proposed to estimate the position of the UAV relative to the target using historical data (estimated distance and relative displacement measurements). Using these estimates, a saturated proportional navigation controller is developed, by which the UAV can approach the target, making the UGV enter the field of view (FOV) of the camera deployed in the UAV. Then, a sensor fusion estimation algorithm based on an extended Kalman filter (EKF) is proposed to achieve accurate landing. Finally, a numerical example and a real experiment are used to support the theoretical results. Published version This work was supported by the National Natural Science Foundation of China (grant: 62003243), the Fundamental Research Funds for the Central Universities (No.: 22120210099), the Shanghai Municipal Commission of Science and Technology (No.: 19511132101), the Shanghai Municipal Science and Technology Major Project (grant: 2021SHZDZX0100), the Shanghai Gaofeng & Gaoyuan Project for University Academic Program Development (No.: 22-3) and the Basic Science Centre Program by the National Natural Science Foundation of China (grant: 62088101). 2024-03-11T06:56:23Z 2024-03-11T06:56:23Z 2023 Journal Article Cheng, C., Li, X., Xie, L. & Li, L. (2023). A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments. Drones, 7(10), 613-. https://dx.doi.org/10.3390/drones7100613 2504-446X https://hdl.handle.net/10356/174004 10.3390/drones7100613 2-s2.0-85175459750 10 7 613 en Drones © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Navigation
Sensor fusion
spellingShingle Engineering
Navigation
Sensor fusion
Cheng, Cheng
Li, Xiuxian
Xie, Lihua
Li, Li
A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments
description This study designs a navigation and landing scheme for an unmanned aerial vehicle (UAV) to autonomously land on an arbitrarily moving unmanned ground vehicle (UGV) in GPS-denied environments based on vision, ultra-wideband (UWB) and system information. In the approaching phase, an effective multi-innovation forgetting gradient (MIFG) algorithm is proposed to estimate the position of the UAV relative to the target using historical data (estimated distance and relative displacement measurements). Using these estimates, a saturated proportional navigation controller is developed, by which the UAV can approach the target, making the UGV enter the field of view (FOV) of the camera deployed in the UAV. Then, a sensor fusion estimation algorithm based on an extended Kalman filter (EKF) is proposed to achieve accurate landing. Finally, a numerical example and a real experiment are used to support the theoretical results.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Cheng, Cheng
Li, Xiuxian
Xie, Lihua
Li, Li
format Article
author Cheng, Cheng
Li, Xiuxian
Xie, Lihua
Li, Li
author_sort Cheng, Cheng
title A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments
title_short A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments
title_full A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments
title_fullStr A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments
title_full_unstemmed A unmanned aerial vehicle (UAV)/unmanned ground vehicle (UGV) dynamic autonomous docking scheme in GPS-denied environments
title_sort unmanned aerial vehicle (uav)/unmanned ground vehicle (ugv) dynamic autonomous docking scheme in gps-denied environments
publishDate 2024
url https://hdl.handle.net/10356/174004
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