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Helmert#039;s and Bowie#039;s geodetic mapping methods and their relation to graph-based SLAM

机译:Helmert和Bowie的大地测量方法及其与基于图的SLAM的关系

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The problem of simultaneously localization a robot and modeling the environment is a prerequisite for several robotic applications and a large variety of solutions have been proposed allowing robots to build maps and use them for navigation. Also the geodetic community addressed large-scale mapping for centuries, computing maps which span across continents. These mapping processes had to deal with several challenges that are similar to those of the robotics community. In this paper, we explain two key geodetic mapping methods that we believe are relevant for robotics. We also aim at providing a geodetic perspective on current state-of-the-art SLAM methods and at identifying similarities between the solutions proposed by both communities. The central goal of this paper is to bring both fields close together and to enable future synergies.
机译:同时定位机器人和对环境建模的问题是一些机器人应用程序的先决条件,并且已经提出了多种解决方案,允许机器人构建地图并将其用于导航。大地测量界也解决了数百年来的大规模制图问题,计算了横跨大洲的地图。这些映射过程必须处理与机器人社区相似的若干挑战。在本文中,我们解释了我们认为与机器人技术相关的两种关键的大地测量方法。我们还旨在提供有关当前最先进的SLAM方法的大地测量观点,并确定两个社区提出的解决方案之间的相似性。本文的主要目标是使这两个领域紧密联系在一起,并实现未来的协同作用。

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