A Vision-Based Method for Determining Aircraft State during Spin Recovery
This article proposes a vision-based method of determining in which of the three states, defined in the spin recovery process, is an aircraft. The correct identification of this state is necessary to make the right decisions during the spin recovery maneuver. The proposed solution employs a keypoint...
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doaj-fda78a66c47e41db8eb1c50aa6d0c0b52020-11-25T02:54:16ZengMDPI AGSensors1424-82202020-04-01202401240110.3390/s20082401A Vision-Based Method for Determining Aircraft State during Spin RecoveryTomasz Kapuscinski0Piotr Szczerba1Tomasz Rogalski2Pawel Rzucidlo3Zygmunt Szczerba4Department of Computer and Control Engineering, Faculty of Electrical and Computer Engineering, Rzeszow University of Technology, W. Pola 2, 35-959 Rzeszow, PolandDepartment of Avionics and Control Systems, Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, Aleja Powstancow Warszawy 12, 35-959 Rzeszow, PolandDepartment of Avionics and Control Systems, Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, Aleja Powstancow Warszawy 12, 35-959 Rzeszow, PolandDepartment of Avionics and Control Systems, Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, Aleja Powstancow Warszawy 12, 35-959 Rzeszow, PolandDepartment of Aerodynamics and Fluid Mechanics, Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, Aleja Powstancow Warszawy 12, 35-959 Rzeszow, PolandThis article proposes a vision-based method of determining in which of the three states, defined in the spin recovery process, is an aircraft. The correct identification of this state is necessary to make the right decisions during the spin recovery maneuver. The proposed solution employs a keypoints displacements analysis in consecutive frames taken from the on-board camera. The idea of voting on the temporary location of the rotation axis and dominant displacement direction was used. The decision about the state is made based on a proposed set of rules employing the histogram spread measure. To validate the method, experiments on flight simulator videos, recorded at varying altitudes and in different lighting, background, and visibility conditions, were carried out. For the selected conditions, the first flight tests were also performed. Qualitative and quantitative assessments were conducted using a multimedia data annotation tool and the Jaccard index, respectively. The proposed approach could be the basis for creating a solution supporting the pilot in the process of aircraft spin recovery and, in the future, the development of an autonomous method.https://www.mdpi.com/1424-8220/20/8/2401aircraft spin recoveryaircraft spin phase detectioncomputer visionimage analysiskeypoints matching |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tomasz Kapuscinski Piotr Szczerba Tomasz Rogalski Pawel Rzucidlo Zygmunt Szczerba |
spellingShingle |
Tomasz Kapuscinski Piotr Szczerba Tomasz Rogalski Pawel Rzucidlo Zygmunt Szczerba A Vision-Based Method for Determining Aircraft State during Spin Recovery Sensors aircraft spin recovery aircraft spin phase detection computer vision image analysis keypoints matching |
author_facet |
Tomasz Kapuscinski Piotr Szczerba Tomasz Rogalski Pawel Rzucidlo Zygmunt Szczerba |
author_sort |
Tomasz Kapuscinski |
title |
A Vision-Based Method for Determining Aircraft State during Spin Recovery |
title_short |
A Vision-Based Method for Determining Aircraft State during Spin Recovery |
title_full |
A Vision-Based Method for Determining Aircraft State during Spin Recovery |
title_fullStr |
A Vision-Based Method for Determining Aircraft State during Spin Recovery |
title_full_unstemmed |
A Vision-Based Method for Determining Aircraft State during Spin Recovery |
title_sort |
vision-based method for determining aircraft state during spin recovery |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-04-01 |
description |
This article proposes a vision-based method of determining in which of the three states, defined in the spin recovery process, is an aircraft. The correct identification of this state is necessary to make the right decisions during the spin recovery maneuver. The proposed solution employs a keypoints displacements analysis in consecutive frames taken from the on-board camera. The idea of voting on the temporary location of the rotation axis and dominant displacement direction was used. The decision about the state is made based on a proposed set of rules employing the histogram spread measure. To validate the method, experiments on flight simulator videos, recorded at varying altitudes and in different lighting, background, and visibility conditions, were carried out. For the selected conditions, the first flight tests were also performed. Qualitative and quantitative assessments were conducted using a multimedia data annotation tool and the Jaccard index, respectively. The proposed approach could be the basis for creating a solution supporting the pilot in the process of aircraft spin recovery and, in the future, the development of an autonomous method. |
topic |
aircraft spin recovery aircraft spin phase detection computer vision image analysis keypoints matching |
url |
https://www.mdpi.com/1424-8220/20/8/2401 |
work_keys_str_mv |
AT tomaszkapuscinski avisionbasedmethodfordeterminingaircraftstateduringspinrecovery AT piotrszczerba avisionbasedmethodfordeterminingaircraftstateduringspinrecovery AT tomaszrogalski avisionbasedmethodfordeterminingaircraftstateduringspinrecovery AT pawelrzucidlo avisionbasedmethodfordeterminingaircraftstateduringspinrecovery AT zygmuntszczerba avisionbasedmethodfordeterminingaircraftstateduringspinrecovery AT tomaszkapuscinski visionbasedmethodfordeterminingaircraftstateduringspinrecovery AT piotrszczerba visionbasedmethodfordeterminingaircraftstateduringspinrecovery AT tomaszrogalski visionbasedmethodfordeterminingaircraftstateduringspinrecovery AT pawelrzucidlo visionbasedmethodfordeterminingaircraftstateduringspinrecovery AT zygmuntszczerba visionbasedmethodfordeterminingaircraftstateduringspinrecovery |
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1724722442210902016 |