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Survey of Geodetic Mapping Methods: Geodetic Approaches to Mapping and the Relationship to Graph-Based SLAM

机译:大地测绘方法概述:大地测绘方法及其与基于图的SLAM的关系

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The ability to simultaneously localize a robot and build a map of the environment is central to most robotics applications, and the problem is often referred to as simultaneous localization and mapping (SLAM). Robotics researchers have proposed a large variety of solutions allowing robots to build maps and use them for navigation. In addition, the geodetic community has addressed large-scale map building for centuries, computing maps that span across continents. These large-scale mapping processes had to deal with several challenges that are similar to those of the robotics community. In this article, we explain key geodetic map building methods that we believe are relevant for robot mapping. We also aim at providing a geodetic perspective on current state-of-the-art SLAM methods and identifying similarities both in terms of challenges faced and the solutions proposed by both communities. The central goal of this article is to connect both fields and enable future synergies between them.
机译:同时定位机器人并构建环境地图的能力是大多数机器人应用程序的核心,该问题通常称为同时定位和地图(SLAM)。机器人研究人员提出了各种各样的解决方案,使机器人可以构建地图并将其用于导航。此外,大地测量界已经解决了数百年来的大规模地图构建问题,计算了横跨大洲的地图。这些大规模的制图过程必须应对与机器人技术界类似的若干挑战。在本文中,我们解释了我们认为与机器人制图有关的关键大地图构建方法。我们还旨在提供有关当前最先进的SLAM方法的大地测量视角,并从面临的挑战和两个社区提出的解决方案方面确定相似之处。本文的主要目标是将这两个领域联系起来,并在它们之间实现未来的协同作用。

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