Ground Speed Optical Estimator for Miniature UAV

Chmielewski, Piotr; Sibilski, Krzysztof

doi:10.3390/s21082754

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…For instance, the UAV used for image acquisition experiences 40 km/h velocity [43]. Chmielewski and Sibilski studied developing an optics-based system to measure the ground velocity of the UAV, and X-UAV Talon EPO was utilized in this study, which exhibited 75 km/h velocity [44]. Mittal and Muneshwar projected the design and development of a miniature UAV called Sparrow S that reaches cruise velocity of 80-90 km/h [45].…”

Section: Numerical Analysismentioning

confidence: 99%

Investigation on Surface Roughness of PolyJet-Printed Airfoil Geometries for Small UAV Applications

Gülcan¹,

Günaydın²,

Çelik³

2022

Aerospace

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The present study focuses on producibility and surface roughness characteristics of airfoil geometries and their effect on aerodynamic performance for different velocities, surface roughness values and angles of attack. Two different tray orientations (along X and Y axis), two different build directions (vertical and horizontal) and two different surface finish settings (matte and glossy) were used to evaluate the effect of these parameters on the surface roughness of both up- and down-facing surfaces of airfoils produced by PolyJet. On both surfaces, surface roughness measurements were performed on two crossing directions. The results showed that horizontal build direction where surfaces of airfoils were parallel to the build platform experienced lower surface roughness than the vertical build direction. Vertically oriented specimens showed a considerable degree of distortions especially in trailing edges along with very high surface irregularities on side walls. In general, glossy or matte finish settings resulted in similar surface roughness values and specimens located along X direction showed better surface quality than specimens located along Y direction with an inconsiderable difference. Besides this, CFD analysis revealed that surface roughness caused by printing strategies directly influences the aerodynamic performance of the fixed-wing UAVs (Unmanned Aerial Vehicles) to considerable degrees. The increase in the drag force coefficient, due to surface roughness, reached almost 7.5% for high cruise velocity at 0° angle of attack and 13% at 10° angle of attack in which stall commences.

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Section: Numerical Analysismentioning

confidence: 99%

Investigation on Surface Roughness of PolyJet-Printed Airfoil Geometries for Small UAV Applications

Gülcan¹,

Günaydın²,

Çelik³

2022

Aerospace

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“…In 2021, Negoro et al [6] proposed a flight speed measurement method based on image processing to calculate the energy model of the UAV. In 2021, Sibilski et al [7] developed an optics-based system to estimate the ground speed of a drone in the event of GNSS failure, jamming, or unavailability.…”

Section: Introductionmentioning

confidence: 99%

Flight state recognition for UAV optical flow velocity measurement

Yang

Liu

2023

J. Phys.: Conf. Ser.

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For the visual navigation and positioning of drones, the optical flow algorithm is used to calculate the flight speed of the drone, the calculation errors of its rotation state, and the vertical take-off and landing state. Based on the characteristics of its optical flow data, this paper compares various classification calculation methods. It uses the median KNN curve of the optical flow vector to simplify its feature quantity. Finally, it realizes the motion of the UAV with the optical flow characteristics based on the SVM algorithm. State recognition experiments have proved that this method can effectively identify the motion state of the UAV, and the calculation efficiency is high.

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“…Optical flow has been widely applied in computer vision and robotics. The object tracking task may involve the feature point tracking of optical flow in the motion-based tracking method [6,7]. The optical flow can also be used to construct the environmental maps and obtain the motion of the camera itself [2,8].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Visual Servoing for Obstacle Avoidance of Micro Unmanned Aerial Vehicle with Optical Flow and Switched System Model

et al. 2021

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A vision-based adaptive switching controller that uses optical flow information to avoid obstacles for micro unmanned aerial vehicles (MUAV) is proposed in this paper. To use the optical flow to indicate the distance between the MUAV and the environment, we propose an algorithm with multi-thread processing such that the optical flow information is obtained reliably and continuously in the entire camera field of view. The flying behavior of considered MUAV is regarded as a switching system when considering different flying modes during the mission of obstacle avoidance. By the required flight direction for obstacle avoidance specified by the detected optical flow, an adaptive control scheme is designed to track the required trajectory in switching modes. The simulation result shows the tracking performances of the adaptive control with the switching system. The experiment of the whole system is completed to verify the obstacle avoidance capability of our system.

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Ground Speed Optical Estimator for Miniature UAV

Cited by 4 publications

References 27 publications

Investigation on Surface Roughness of PolyJet-Printed Airfoil Geometries for Small UAV Applications

Investigation on Surface Roughness of PolyJet-Printed Airfoil Geometries for Small UAV Applications

Flight state recognition for UAV optical flow velocity measurement

Adaptive Visual Servoing for Obstacle Avoidance of Micro Unmanned Aerial Vehicle with Optical Flow and Switched System Model

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