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An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad

In this paper, an onboard vision-based system for the autonomous landing of a low-cost quadrotor is presented. A novel landing pad with different optical markers sizes is carefully designed to be robustly recognized at different distances. To provide reliable pose information in a GPS (Global Positi...

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Detalles Bibliográficos
Autores principales: Liu, Xuancen, Zhang, Shifeng, Tian, Jiayi, Liu, Longbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874798/
https://www.ncbi.nlm.nih.gov/pubmed/31671894
http://dx.doi.org/10.3390/s19214703
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author Liu, Xuancen
Zhang, Shifeng
Tian, Jiayi
Liu, Longbin
author_facet Liu, Xuancen
Zhang, Shifeng
Tian, Jiayi
Liu, Longbin
author_sort Liu, Xuancen
collection PubMed
description In this paper, an onboard vision-based system for the autonomous landing of a low-cost quadrotor is presented. A novel landing pad with different optical markers sizes is carefully designed to be robustly recognized at different distances. To provide reliable pose information in a GPS (Global Positioning System)-denied environment, a vision algorithm for real-time landing pad recognition and pose estimation is implemented. The dynamic model of the quadrotor is established and a system scheme for autonomous landing control is presented. A series of autonomous flights have been successfully performed, and a video of the experiment is available online. The efficiency and accuracy of the presented vision-based system is demonstrated by using its position and attitude estimates as control inputs for the autonomous landing of a self-customized quadrotor.
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spelling pubmed-68747982019-12-09 An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad Liu, Xuancen Zhang, Shifeng Tian, Jiayi Liu, Longbin Sensors (Basel) Article In this paper, an onboard vision-based system for the autonomous landing of a low-cost quadrotor is presented. A novel landing pad with different optical markers sizes is carefully designed to be robustly recognized at different distances. To provide reliable pose information in a GPS (Global Positioning System)-denied environment, a vision algorithm for real-time landing pad recognition and pose estimation is implemented. The dynamic model of the quadrotor is established and a system scheme for autonomous landing control is presented. A series of autonomous flights have been successfully performed, and a video of the experiment is available online. The efficiency and accuracy of the presented vision-based system is demonstrated by using its position and attitude estimates as control inputs for the autonomous landing of a self-customized quadrotor. MDPI 2019-10-29 /pmc/articles/PMC6874798/ /pubmed/31671894 http://dx.doi.org/10.3390/s19214703 Text en © 2019 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Xuancen
Zhang, Shifeng
Tian, Jiayi
Liu, Longbin
An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad
title An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad
title_full An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad
title_fullStr An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad
title_full_unstemmed An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad
title_short An Onboard Vision-Based System for Autonomous Landing of a Low-Cost Quadrotor on a Novel Landing Pad
title_sort onboard vision-based system for autonomous landing of a low-cost quadrotor on a novel landing pad
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874798/
https://www.ncbi.nlm.nih.gov/pubmed/31671894
http://dx.doi.org/10.3390/s19214703
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