Observability analysis of SLAM using fisher information matrix
Observability analysis of SLAM using fisher information matrix
复制标题
利用渔民信息矩阵进行SLAM的可观测性分析
DOI：
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复制
发表时间：
2008
期刊：
影响因子：
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通讯作者：
G. Dissanayake
中科院分区：
文献类型：
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作者：
Zhan Wang;G. Dissanayake
本文提出了一种新的方法来评估可观测性的同时定位和地图（SLAM）问题。SLAM问题的估计理论公式的状态向量被重铸，以包括从其中进行测量的所有机器人姿势。这将SLAM转换为估计一组未知的恒定随机变量的问题。推导并分析了静态估计问题的Fisher信息矩阵，以检验SLAM的可观测性。结果的分析和比较，在最近的文献中提出的可观测性分析。所提出的技术使得有可能分析一系列的SLAM问题的可观测性。
This paper presents a new technique for evaluating the observability of the simultaneous localization and mapping (SLAM) problem. The state vector of an estimation theoretic formulation of the SLAM problem is recast to include all robot poses from which the measurements are made. This converts SLAM to a problem of estimating a set of unknown, constant random variables. Fisher Information Matrix of the resulting static estimation problem is derived and analyzed to examine the observability of SLAM. Outcomes of the analysis and comparisons to the observability analysis presented in recent literature are presented. Proposed technique makes it possible to analyze the observability of a range of SLAM problems with ease.