带lms传感器的移动机器人rbpf-slam在室内环境中的应用

2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B) Pub Date : 2017-10-01 DOI:10.1109/ICEE-B.2017.8192121

A. Hentout, Abdelkader Beghni, Abdelkader Benahmed Nourine, Abderraouf Maoudj, B. Bouzouia

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引用次数: 1

摘要

近年来，同步定位与映射(SLAM)问题成为移动机器人领域的研究热点。另外，引入Rao-Blackwellized Particle Filter (RBPF)作为解决这一问题的有效手段。本文描述了一种基于RBPF-SLAM的移动机器人姿态估计方法的实现，同时构建其周围室内环境的地图。在这种方法中，RBPF中的每个粒子代表一个单独的环境地图和机器人的可能轨迹。该方法在罗布特移动机器人上进行了实现和测试，同时利用了装备它的LMS传感器提供的数据。实验结果表明，所提出的RBPF-SLAM在(i)生成地图的精度和(ii)机器人实际姿态的计算方面是有效的。

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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Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot

Recently, Simultaneous Localization And Mapping (SLAM) problem becomes an active research field in mobile robotics. In addition, Rao-Blackwellized Particle Filter (RBPF) has been introduced as an effective means to solve this problem. This paper describes the implementation of a RBPF-SLAM to estimate the mobile robot pose while building the map of its surrounding indoor environment. In this approach, each particle in RBPF represents an individual map of the environment and a possible trajectory of the robot. This method is implemented and tested on the RobuTER mobile robot while exploiting the data delivered by the LMS sensor equipping it. The experimental results show the effectiveness of the proposed RBPF-SLAM in terms of (i) accuracy of the generated maps and (ii) the calculation of the actual robot pose.

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2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)

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