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On simulation and analysis of mobile robot SLAM using Rao-Blackwellized particle filters

机译:Rao-Blackwellized粒子滤波器对移动机器人SLAM的仿真与分析

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摘要

The simultaneous localization and mapping (SLAM) is considered as a crucial prerequisite for purely autonomous mobile robots. In this paper, we demonstrate the mobile robot SLAM using Rao-Blackwellized particle filters (RBPF) through computer simulations under MATLAB platform, while an analytical investigation into the involved algorithms is presented. Then we make further comparisons, not only in parallel between the FastSLAM 1.0 and FastSLAM 2.0, also in vertical between FastSLAM performance and EKF-SLAM performance which used to be the dominant approach to the SLAM problem. Vivid simulations and numerical analysis make the paper illustrated with clarity and perception.
机译:同时定位和映射(SLAM)被认为是纯自主移动机器人的关键先决条件。在本文中,我们通过在MATLAB平台下进行计算机仿真,演示了使用Rao-Blackwellized粒子滤波器(RBPF)的移动机器人SLAM,同时对相关算法进行了分析研究。然后,我们不仅在FastSLAM 1.0和FastSLAM 2.0之间进行并行比较,而且在FastSLAM性能和EKF-SLAM性能之间进行垂直比较,这些曾经是SLAM问题的主要解决方法。生动的模拟和数值分析使论文清晰易懂。

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