Measurement of Unmanned Aerial Vehicle Attitude Angles Based on a Single Captured Image

Zhang, Jin; Ren, Lijun; Deng, Huaxia; Zhong, Xiang; Wen, Pengcheng

doi:10.3390/s18082655

Cited by 25 publications

(11 citation statements)

References 25 publications

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“…Consequently, this method has become highly advanced with extensive application in various fields such as industry [ 5 , 6 , 7 ], civil infrastructure [ 8 , 9 ], food [ 10 ], medicine health [ 11 , 12 ], transport [ 13 , 14 , 15 ], security surveillance, etc. Particularly, the vision-based measurement techniques have gathered increasing attention in aerospace research and applications [ 16 , 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under Challenging Conditions

Liu

Guo

et al. 2021

Sensors

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Coded targets have been demarcated as control points in various vision measurement tasks such as camera calibration, 3D reconstruction, pose estimation, etc. By employing coded targets, matching corresponding image points in multi images can be automatically realized which greatly improves the efficiency and accuracy of the measurement. Although the coded targets are well applied, particularly in the industrial vision system, the design of coded targets and its detection algorithms have encountered difficulties, especially under the conditions of poor illumination and flat viewing angle. This paper presents a novel concentric circular coded target (CCCT), and its positioning and identifying algorithms. The eccentricity error has been corrected based on a practical error-compensation model. Adaptive brightness adjustment has been employed to address the problems of poor illumination such as overexposure and underexposure. The robust recognition is realized by perspective correction based on four vertices of the background area in the CCCT local image. The simulation results indicate that the eccentricity errors of the larger and smaller circles at a large viewing angle of 70° are reduced by 95% and 77% after correction by the proposed method. The result of the wing deformation experiment demonstrates that the error of the vision method based on the corrected center is reduced by up to 18.54% compared with the vision method based on only the ellipse center when the wing is loaded with a weight of 6 kg. The proposed design is highly applicable, and its detection algorithms can achieve accurate positioning and robust identification even in challenging environments.

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Section: Introductionmentioning

confidence: 99%

A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under Challenging Conditions

Liu

Guo

et al. 2021

Sensors

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show abstract

“…Zhang et al proposed a method for attitude angle measurement using a single captured image to assist with the landing of small-scale fixed-wing UAVs. The method has the advantage that the attitude angles are obtained from just one image containing five coded landmarks, which reduces the time to solve the attitude angle while having more than one image in most methods [16]. These kinds of methods require the manual setting of landmarks to deal with the corresponding problems.…”

Section: Introductionmentioning

confidence: 99%

Feature Point Registration Model of Farmland Surface and Its Application Based on a Monocular Camera

Huang

et al. 2020

Sensors

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In this study, an image registration algorithm was applied to calculate the rotation angle of objects when matching images. Some commonly used image feature detection algorithms such as features from accelerated segment test (FAST), speeded up robust features (SURF) and maximally stable extremal regions (MSER) algorithms were chosen as feature extraction components. Comparing the running time and accuracy, the image registration algorithm based on SURF has better performance than the other algorithms. Accurately obtaining the roll angle is one of the key technologies to improve the positioning accuracy and operation quality of agricultural equipment. To acquire the roll angle of agriculture machinery, a roll angle acquisition model based on the image registration algorithm was built. Then, the performance of the model with a monocular camera was tested in the field. The field test showed that the average error of the rolling angle was 0.61°, while the minimum error was 0.08°. The field test indicated that the model could accurately obtain the attitude change trend of agricultural machinery when it was working in irregular farmlands. The model described in this paper could provide a foundation for agricultural equipment navigation and autonomous driving.

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“…Thus, the monocular vision pose measurement can be used to measure the pose between the packaging container and the sample return container (Wang et al, 2019). At present, monocular vision pose measurement methods are mostly based on point features (Zhang et al, 2018;David et al, 2004;Ning et al, 2018). Given a set of 3D points (e.g., marks and corners) and their corresponding 2D points, the pose of the target object can be solved.…”

Section: Introductionmentioning

confidence: 99%

Coaxiality Calculation Method for Dropping Operation of Lunar Surface Sampling Mission Based on Monocular Vision Using Ellipse and Line Features

Wan

Liu

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In the lunar surface sampling mission, the drop operation that transferring the packaging container into the sample return container is a vital step. In this paper, for supporting the drop operation, we proposed a method to measure the coaxiality between the two containers based on the monocular vision pose measurement using ellipse and line features. The method first extracts ellipse and line features in the 2D image to calculate the initial parameters. Then, the initial parameters and the point set are used to fit the curve by the cylinder perspective contours fitting method, where the constraints between ellipse and line features are used to improve the robustness to varying noises. Next, given the fitting ellipse and camera parameters, the pose of the packaging container is solved by using circle-based method. Finally, the coaxiality of the two containers is calculated based on the relative pose between them. Simulation experiments were carried out and the results show the effectiveness and reliability of the proposed method.

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Measurement of Unmanned Aerial Vehicle Attitude Angles Based on a Single Captured Image

Cited by 25 publications

References 25 publications

A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under Challenging Conditions

A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under Challenging Conditions

Feature Point Registration Model of Farmland Surface and Its Application Based on a Monocular Camera

Coaxiality Calculation Method for Dropping Operation of Lunar Surface Sampling Mission Based on Monocular Vision Using Ellipse and Line Features

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