地面和无人机平台之间基于视觉和uwb的协同定位

A. Masiero, C. Toth, F. Remondino
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引用次数: 0

摘要

自主地面车辆技术(AV)的快速发展和最近无人机系统(UAS)应用的激增促使人们寻求适当的解决方案,以确保此类自主平台在任何作战环境和条件下(包括空中和地面平台共享同一空间的情况下)安全有效地导航。由于民用GNSS(全球导航卫星系统)易于获得和效率高,GNSS定位已广泛用于各种消费应用,特别是在移动设备中,事实上,它已成为许多应用的使能技术,几乎可以在任何地方对地面和空中平台进行定位和导航。由于在城市和植被覆盖地区以及信号受到无意和有意干扰时无法保证可靠的GNSS信号接收,因此长期以来,提供替代和互补的定位解决方案一直是人们高度关注的问题。其中一种适用的技术是使用协同导航(CN),其中在近距离航行的平台可以共享导航信息,联合导航解决方案可以为所有平台提供更好的单独导航解决方案。在这项工作中,我们研究了在地面和机载车辆在同一空间运行的区域中CN的可行性和性能。通过多辆地面车辆和无人机的现场测试,获取实验数据,评估网络在模拟路口区域的准确性、鲁棒性和准确性。报告了本研究工作的初步结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vision and UWB-Based Collaborative Positioning Between Ground and UAS Platforms
The rapid development of autonomous ground vehicle technologies (AV) and the recent proliferation of unmanned aerial system (UAS) applications motivate the search for appropriate solutions ensuring safe and effective navigation of such autonomous platforms in any operational environment and condition, including situations where air and ground platforms share the same space. Because of the easy availability and efficiency of GNSS (Global Navigation satellite System) for civilian use, GNSS positioning has been widely used in a large variety of consumer applications, in particular in mobile devices and, in fact, it has become an enabling technology for many applications, allowing positioning and navigation of ground and aerial platforms almost everywhere. Since reliable GNSS signal reception cannot be guaranteed in urban and vegetated areas as well as when signals are subject to unintentional and intentional interferences, the provision of alternate and complementary positioning solutions has been of high interest for a long while. One of the applicable techniques is the use of collaborative navigation (CN), where platforms navigating in close vicinity can share navigation information and a joint navigation solution can potentially provide better individual navigation solutions for all platforms. In this work we investigate the feasibility and performance of CN in areas where ground and airborne vehicles operate in the same space. A field test, including multiple ground vehicles and drones was conducted to acquire experimental data to assess accuracy, robustness and accuracy of CN in a simulated intersection area. Initial results of this research work are reported.
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