A novel framework for UAV returning based on FPGA
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A novel framework for UAV returning based on FPGA Qunfang He1 · Wenjie Chen1 · Danping Zou2 · Zhilei Chai3 Accepted: 12 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
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). Keywords FPGA · UAV · KLT · Hardware and software co-design
* Wenjie Chen [email protected] Qunfang He [email protected] Danping Zou [email protected] Zhilei Chai [email protected] 1
National Trusted Embedded Software Engineering Technology Research Center, East China Normal University, Shanghai, China
2
Shanghai Jiao Tong University, Shanghai, China
3
Jiangnan University, Wuxi, China
13
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Q. He et al.
1 Introduction At present, most unmanned aerial vehicle (UAVs) returning systems rely on the global positioning system (GPS) [21], which makes it possible to hijack a UAV by sending a fake GPS signal to spoof it away from its original flight route [9]. To avoid GPS hijacking, a returning framework independent of GPS signals is particularly important [23]. For example, Warren et al. [30] presented a vision-based route-following system for the free, safe return of UAVs under primary navigation failure, such as GPS jamming. Nevertheless, the system is aimed at a fixed returning route. In other words, the returning system is not suitable for a new flight route. For a UAV returning system, the practicability, real time of the vision algorithm and the height and speed of the UAV must be considered. It is very important to choose a suitable visual algorithm for the UAV returning framework. The adaptability, practicality and low latency of the visual algorithm are the main technical indexes for evaluating the framework [29]. Here, the scene matching algorithm is selected. There are three types of scene matching algorithms: region-based, feature-based and interpretation-based, among which the feature-based scene matching algorithm has the most apparent matching effect. To date, many excellent feature matchi
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