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Titlebook: Switchable Constraints for Robust Simultaneous Localization and Mapping and Satellite-Based Localiza; Niko Sünderhauf Book 2023 Springer N

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發(fā)表于 2025-3-21 18:18:41 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Switchable Constraints for Robust Simultaneous Localization and Mapping and Satellite-Based Localiza
編輯Niko Sünderhauf
視頻videohttp://file.papertrans.cn/884/883749/883749.mp4
概述Presents recent research in robust optimization for Simultaneous Localization and Mapping.Includes a well-written and comprehensive historical overview and tutorial.Proposes an optimization framework
叢書名稱Springer Tracts in Advanced Robotics
圖書封面Titlebook: Switchable Constraints for Robust Simultaneous Localization and Mapping and Satellite-Based Localiza;  Niko Sünderhauf Book 2023 Springer N
描述.Simultaneous Localization and Mapping (SLAM) has been a long-standing research problem in robotics. It describes the problem of a robot mapping an unknown environment, while simultaneously localizing in it with the help of the incomplete map. This book describes a technique called?Switchable Constraints.Switchable Constraints help to increase the robustness of SLAM against data association errors and in particular against false positive loop closure detections. Such false positive loop closure detections can occur when the robot erroneously assumes it re-observed a landmark it has already mapped or when the appearance of the observed surroundings is very similar to the appearance of other places in the map. Ambiguous observations and appearances are very common in human-made environments such as office floors or suburban streets, making robustness against spurious observations a key challenge in SLAM. The book summarizes the foundations of factor graph-based SLAM techniques. Itexplains the problem of data association errors before introducing the novel idea of Switchable Constraints. We present a mathematical derivation and probabilistic interpretation of Switchable Constraints al
出版日期Book 2023
關(guān)鍵詞3D SLAM; Footslam; Monte Carlo Localization; Non-Gaussian Error Characteristics; Robot Localization; Robo
版次1
doihttps://doi.org/10.1007/978-3-031-24017-1
isbn_ebook978-3-031-24017-1Series ISSN 1610-7438 Series E-ISSN 1610-742X
issn_series 1610-7438
copyrightSpringer Nature Switzerland AG 2023
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 20:43:35 | 只看該作者
https://doi.org/10.1007/978-3-031-24017-13D SLAM; Footslam; Monte Carlo Localization; Non-Gaussian Error Characteristics; Robot Localization; Robo
板凳
發(fā)表于 2025-3-22 02:06:44 | 只看該作者
Introduction,In the beginning, robots were in the factories, assembling our cars. Now they are in our homes, vacuuming our floors.
地板
發(fā)表于 2025-3-22 07:01:01 | 只看該作者
,Simultaneous Localization and?Mapping,The problem of simultaneous localization and mapping (SLAM) is an old problem in mobile robotics.
5#
發(fā)表于 2025-3-22 12:18:09 | 只看該作者
Least Squares Optimization,The last chapter concluded with a nonlinear least squares formulation of the (full) SLAM problem and provided an intuitive analogy that helps to understand the general idea behind this formulation.
6#
發(fā)表于 2025-3-22 16:44:01 | 只看該作者
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發(fā)表于 2025-3-23 00:18:26 | 只看該作者
Evaluation,The previous chapter proposed a novel approach for a robust back-end for graph-based SLAM systems. While the general feasibility was shown using a simple example, this chapter will provide a more elaborate evaluation and analysis of the performance of the proposed system.
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發(fā)表于 2025-3-23 03:28:55 | 只看該作者
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發(fā)表于 2025-3-23 09:28:03 | 只看該作者
,Applications Beyond SLAM—Multipath Mitigation in?GNSS-Based Localization Problems Using the?Robust The previous chapters evaluated the proposed robust back-end in a variety of SLAM scenarios and demonstrated its feasibility.
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