Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging

Xiuchuan Xie, Tao Yang, Yanning Zhang, Bang Liang, Linfeng Liu
<span title="2021-05-30">2021</span> <i title="Institution of Engineering and Technology (IET)"> <a target="_blank" rel="noopener" href="" style="color: black;">IET Computer Vision</a> </i> &nbsp;
Small unmanned aerial vehicles (UAVs) have developed rapidly and are widely used for disaster relief, traffic monitoring and military surveillance. To perform these tasks better, it is necessary to improve the environmental perception ability of UAVs in a dynamic environment, including their static and dynamic perception ability. Specifically, both three-dimensional reconstruction for a static scene and localization for moving objects are required. Simultaneous Localization And Mapping
more &raquo; ... y has made great progress in static scene structure reconstruction and UAV self-motion estimation. However, accurate real-time localization of moving objects is still challenging. In this article, a global averaging based localization method is proposed to locate moving objects for a small UAV platform. Inspired by global structure from motion, this idea is applied to the localization of moving objects. To solve moving object localization, the relative motion estimation and global position optimisation methods are proposed. The proposed method was tested in various scenarios with a several trajectories. The extensive experimental results demonstrate the robustness and effectiveness of the proposed method. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1049/cvi2.12053</a> <a target="_blank" rel="external noopener" href="">fatcat:o6ufggf5z5gc7px6ugmwpk57xu</a> </span>
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