Fusion of dependent information in posegraphs

S. Julier
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引用次数: 3

Abstract

In this paper, we consider the problem of fusing measurements which contain correlated noises within posegraph-based formulations of filtering and estimation problems. We develop a formulation of the Weighted Geometric Density (WGD) fusion algorithm, a generalisation of Covariance Intersection (CI), for posegraphs. We show that this form can generate covariance consistent estimates. We propose two methods for computing the weighting parameters by maximising the information or maximising the likelihood.
波塞图中相关信息的融合
在本文中,我们考虑了在基于posegraphy的滤波和估计问题的公式中包含相关噪声的测量融合问题。我们开发了加权几何密度(WGD)融合算法的公式,这是协方差交集(CI)的推广,用于波塞图。我们证明这种形式可以产生协方差一致估计。我们提出了两种计算加权参数的方法,即最大化信息或最大化似然。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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