Deterministic Method of Visual Servoing: Robust Object Tracking by Drone

Ouchatti Zakaria, Bensaid Alaa, M. Fouad, Medromi Hicham
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引用次数: 3

Abstract

This work is part of an application context, focused on the analysis of images flow acquired by a camera embedded in a drone, controlled by a control station. Specifically, we are interested in the coupling vision-command, in order to develop a control system that allows an autonomous navigation and operation of the Unmanned Aerial Vehicle in complex environments where the use of visual sensors appears to be essential for moving the drone in a controlled manner but also to be capable of increasing the stability of the UAV. We propose the state of the art in image-based visual servoing, focused on the control of unmanned aerial vehicles and allows moving from a current position to a desired position according the observed scene while also improving the flight performance (stability and accuracy). Our contribution will be in the proposal of a control approach capable to tracking an object by introducing the concept of real-time and subsequently uses a visual memory in the form of keyframes to automatically reproduce a route already made.
视觉伺服的确定性方法:无人机鲁棒目标跟踪
这项工作是应用环境的一部分,重点是分析由控制站控制的无人机中嵌入的摄像头获取的图像流。具体来说,我们对耦合视觉-命令感兴趣,以便开发一种控制系统,允许无人机在复杂环境中自主导航和操作,其中使用视觉传感器似乎对于以受控方式移动无人机至关重要,但也能够增加无人机的稳定性。我们提出了基于图像的视觉伺服技术,专注于无人机的控制,并允许根据观察到的场景从当前位置移动到期望位置,同时还提高了飞行性能(稳定性和准确性)。我们的贡献将是提出一种控制方法,能够通过引入实时概念来跟踪对象,随后使用关键帧形式的视觉记忆来自动复制已经制作的路线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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