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A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light de...

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Detalles Bibliográficos
Autores principales: Lyu, Pin, Wang, Bingqing, Lai, Jizhou, Liu, Shichao, Li, Zhimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806240/
https://www.ncbi.nlm.nih.gov/pubmed/31597280
http://dx.doi.org/10.3390/s19194337
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author Lyu, Pin
Wang, Bingqing
Lai, Jizhou
Liu, Shichao
Li, Zhimin
author_facet Lyu, Pin
Wang, Bingqing
Lai, Jizhou
Liu, Shichao
Li, Zhimin
author_sort Lyu, Pin
collection PubMed
description In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme.
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spelling pubmed-68062402019-11-07 A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors Lyu, Pin Wang, Bingqing Lai, Jizhou Liu, Shichao Li, Zhimin Sensors (Basel) Article In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme. MDPI 2019-10-08 /pmc/articles/PMC6806240/ /pubmed/31597280 http://dx.doi.org/10.3390/s19194337 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
Lyu, Pin
Wang, Bingqing
Lai, Jizhou
Liu, Shichao
Li, Zhimin
A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors
title A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors
title_full A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors
title_fullStr A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors
title_full_unstemmed A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors
title_short A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors
title_sort drag model-lidar-imu fault-tolerance fusion method for quadrotors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806240/
https://www.ncbi.nlm.nih.gov/pubmed/31597280
http://dx.doi.org/10.3390/s19194337
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