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Distributed Joint Mapping and Registration with Limited Fields-of-View

机译:有限视野的分布式联合制图和配准

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The interest of this paper is to fuse maps, expressed in different local coordinates, of multiple mobile agents with limited fields-of-view, without knowledge of the relative poses among agents. To this end, the map is modeled as a multi-object Poisson process and a recently developed approach, named Cauchy-Schwarz fusion (CSF), is adopted. In order to perform calibration among local coordinates, the information-theoretic interpretation of CSF is exploited to build a suitable map discrepancy to be minimized with respect to the drift and orientation parameters. A multi-hypothesis method is adopted in order to efficiently solve the resulting optimization problem.
机译:本文的目的是在不了解智能体之间的相对姿势的情况下,融合视野有限的多个移动智能体的地图,这些地图以不同的局部坐标表示。为此,将地图建模为多对象泊松过程,并采用了最近开发的名为Cauchy-Schwarz融合(CSF)的方法。为了在局部坐标之间执行校准,利用CSF的信息理论解释来建立合适的地图差异,以最大程度地减少漂移和方向参数。为了有效地解决由此产生的优化问题,采用了一种多假设方法。

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