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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-6806240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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