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Erschienen in: The Journal of Supercomputing 5/2021

25.09.2020

A novel framework for UAV returning based on FPGA

verfasst von: Qunfang He, Wenjie Chen, Danping Zou, Zhilei Chai

Erschienen in: The Journal of Supercomputing | Ausgabe 5/2021

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Abstract

To date, most unmanned aerial vehicle (UAV) returning technology has relied on the global positioning system (GPS). The risk is that the UAV may be spoofed by fake GPS signals, which could cause it to deviate from its expected flight route. Therefore, a returning framework without GPS is particularly essential. To address this issue, this paper proposes a new UAV returning framework based on improved Kanade–Lucas–Tomasi (KLT) feature tracker. This framework addresses the issues of high computational complexity of KLT by using a field-programmable gate array and designs the hardware acceleration architecture by integrating several optimization methods. Moreover, it adopts hardware/software co-design technology to improve parallelism and resource utilization. With these optimizations, the framework can be deployed on most development boards with flexible hardware resources. Finally, the effectiveness of the improved algorithm are demonstrated using zedboard development board, and the results show that the processing speed can achieve 60 frames per second (fps).

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Metadaten
Titel
A novel framework for UAV returning based on FPGA
verfasst von
Qunfang He
Wenjie Chen
Danping Zou
Zhilei Chai
Publikationsdatum
25.09.2020
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 5/2021
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-020-03434-4

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