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Localization Framework for Real-Time UAV Autonomous Landing: An On-Ground Deployed Visual Approach

机译:实时无人机自主着陆的本地化框架:一种地面部署的可视化方法

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摘要

One of the greatest challenges for fixed-wing unmanned aircraft vehicles (UAVs) is safe landing. Hereafter, an on-ground deployed visual approach is developed in this paper. This approach is definitely suitable for landing within the global navigation satellite system (GNSS)-denied environments. As for applications, the deployed guidance system makes full use of the ground computing resource and feedbacks the aircraft’s real-time localization to its on-board autopilot. Under such circumstances, a separate long baseline stereo architecture is proposed to possess an extendable baseline and wide-angle field of view (FOV) against the traditional fixed baseline schemes. Furthermore, accuracy evaluation of the new type of architecture is conducted by theoretical modeling and computational analysis. Dataset-driven experimental results demonstrate the feasibility and effectiveness of the developed approach.
机译:固定翼无人飞行器(UAV)的最大挑战之一是安全着陆。此后,本文开发了一种地面部署的视觉方法。这种方法绝对适合在拒绝使用全球导航卫星系统(GNSS)的环境中着陆。对于应用程序,已部署的制导系统会充分利用地面计算资源,并将飞机的实时定位反馈到机载自动驾驶仪上。在这种情况下,与传统的固定基线方案相比,提出了一种单独的长基线立体声架构,该体系具有可扩展的基线和广角视场(FOV)。此外,通过理论建模和计算分析对新型架构进行准确性评估。数据集驱动的实验结果证明了该方法的可行性和有效性。

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