Design, aerodynamic analysis and test flight of a bat-inspired tailless flapping wing unmanned aerial vehicle

Bie, Dawei; Li, Daochun; Xiang, Jiawei; Li, Huadong; Kan, Zi; Sun, Yi

doi:10.1016/j.ast.2021.106557

Cited by 43 publications

(12 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A raster data-cutting tool was used to cut the research area according to the square, and 16 regular rectangular images with the size of 2136 × 2629 pixels were obtained. A Python script was written to convert 16-scene 32-bit images into 8-bit images in batches, which was convenient for the normalization of UAV multi-band orthophoto images [41,42].…”

Section: Data Processingmentioning

confidence: 99%

Economic Fruit Forest Classification Based on Improved U-Net Model in UAV Multispectral Imagery

Jia

Yang

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Economic fruit forest is an important part of Chinese agriculture with high economic value and ecological benefits. Using UAV multi-spectral images to research the classification of economic fruit forests based on deep learning is of great significance for accurately understanding the distribution and scale of fruit forests and the status quo of national economic fruit forest resources. Based on the multi-spectral remote sensing images of UAV, this paper constructed semantic segmentation data of economic fruit forests, conducted a comparative study on the classification and identification of economic fruit forests of FCN, SegNet, and U-Net classic semantic segmentation models, and proposed an improved ISDU-Net model. The recognition accuracies of the ISDU-Net were 87.73%, 70.68%, 78.69%, and 0.84, respectively, in terms of pixel accuracy, average intersection ratio, frequency weight intersection ratio, and Kappa coefficient, which were 3.19%, 8.90%, and 4.51% higher than the original U-Net model. The results showed that the improved ISDU-Net could effectively improve the learning ability of the model, perform better in the prediction of short sample categories, obtain a higher classification accuracy of fruit forest crops, and provide a new idea for the research on accurate fruit forest identification.

show abstract

Section: Data Processingmentioning

confidence: 99%

Economic Fruit Forest Classification Based on Improved U-Net Model in UAV Multispectral Imagery

Jia

Yang

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Most bionic systems took the bionic idea to guide the design in mechanical-inspired way [7][8][9] and functional-inspired way [10][11][12][13][14][15]. As for biomimetic visual system, Duan et al [10] designed the bionic perception system for aircraft refuelling target detection, and the attention mechanism of raptors' eye was the key point for accurate detection.…”

Section: Biomimetic Visual Systemmentioning

confidence: 99%

“…Most bionic systems took the bionic idea to guide the design in mechanical‐inspired way [7–9] and functional‐inspired way [10–15]. As for biomimetic visual system, Duan et al.…”

Section: Related Workmentioning

confidence: 99%

Hawk‐eye‐inspired perception algorithm of stereo vision for obtaining orchard 3D point cloud navigation map

Zhang

Chen

et al. 2022

CAAI Trans on Intel Tech

View full text Add to dashboard Cite

The binocular stereo vision is the lowest cost sensor for obtaining 3D information. Considering the weakness of long-distance measurement and stability, the improvement of accuracy and stability of stereo vision is urgently required for application of precision agriculture. To address the challenges of stereo vision long-distance measurement and stable perception without hardware upgrade, inspired by hawk eyes, higher resolution perception and the adaptive HDR (High Dynamic Range) were introduced in this paper. Simulating the function from physiological structure of 'deep fovea' and 'shallow fovea' of hawk eye, the higher resolution reconstruction method in this paper was aimed at accuracy improving. Inspired by adjustment of pupils, the adaptive HDR method was proposed for high dynamic range optimisation and stable perception. In various light conditions, compared with default stereo vision, the accuracy of proposed algorithm was improved by 28.0% evaluated by error ratio, and the stability was improved by 26.56% by disparity accuracy. For fixed distance measurement, the maximum improvement was 78.6% by standard deviation. Based on the hawk-eye-inspired perception algorithm, the point cloud of orchard was improved both in quality and quantity. The hawk-eye-inspired perception algorithm contributed great advance in binocular 3D point cloud reconstruction in orchard navigation map. K E Y W O R D S adaptive high dynamic range, binocular stereo vision, hawk-eye-inspired perception, point cloud of orchard, super-resolution generative adversarial network 1 | INTRODUCTION Precision agriculture needs accurate perception. In orchard automation agricultural production, accurate and stable 3D navigation map is the basis of UAV and unmanned vehicle operation [1]. Agricultural production is very sensitive to the cost. Binocular stereo vision has advantages over other sensors because of low cost, high sampling frequency, large amount of data obtaining ability, low-power consumption, and light weight, which is widely used in the all-production links in smart agriculture [2, 3]. However, in most condition of agricultural outdoor working environment, optical sensors and This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

“…With the advancement of science, engineering, and technology, a growing number of robots have been designed in different shapes and sizes to mimic biological systems [3,4]. These biomimetic robots mimic animals, such as four-legged animals (quadrupeds) [5], monkeys [6], snakes [7], fish [8,9], bats [10,11], and various birds and insects [12][13][14]. These robots have diverse potential applications, ranging from simple toys to exploration robots in dangerous and hazardous environments.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal Mode System Identification of an Insect-like Tailless Flapping-Wing Micro Air Vehicle Using Onboard Sensors

Aurecianus

Park

et al. 2022

Applied Sciences

View full text Add to dashboard Cite

In this paper, model parameter identification results are presented for a longitudinal mode dynamic model of an insect-like tailless flapping-wing micro air vehicle (FWMAV) using angle and angular rate data from onboard sensors only. A gray box model approach with indirect method was utilized with adaptive Gauss–Newton, Levenberg–Marquardt, and gradient search identification methods. Regular and low-frequency reference commands were mainly used for identification since they gave higher fit percentages than irregular and high-frequency reference commands. Dynamic parameters obtained using three identification methods with two different datasets were similar to each other, indicating that the obtained dynamic model was sufficiently reliable. Most of the identified dynamic model parameters had similar values to the computationally obtained ones, except stability derivatives for pitching moment with forward velocity and pitching rate variations. Differences were mainly due to certain neglected body, nonlinear dynamics, and the shift of the center of gravity. Fit percentage of the identified dynamic model (~49%) was more than two-fold higher than that of the computationally obtained one (~22%). Frequency domain analysis showed that the identified model was much different from that of the computationally obtained one in the frequency range of 0.3 rad/s to 5 rad/s, which affected transient responses. Both dynamic models showed that the phase margin was very low, and that it should be increased by a feedback controller to have a robustly stable system. The stable dominant pole of the identified model had a higher magnitude which resulted in faster responses. The identified dynamic model exhibited much closer responses to experimental flight data in pitching motion than the computationally obtained dynamic model, demonstrating that the identified dynamic model could be used for the design of more effective pitch angle-stabilizing controllers.

show abstract

Design, aerodynamic analysis and test flight of a bat-inspired tailless flapping wing unmanned aerial vehicle

Cited by 43 publications

References 28 publications

Economic Fruit Forest Classification Based on Improved U-Net Model in UAV Multispectral Imagery

Economic Fruit Forest Classification Based on Improved U-Net Model in UAV Multispectral Imagery

Hawk‐eye‐inspired perception algorithm of stereo vision for obtaining orchard 3D point cloud navigation map

Longitudinal Mode System Identification of an Insect-like Tailless Flapping-Wing Micro Air Vehicle Using Onboard Sensors

Contact Info

Product

Resources

About