Research on simultaneous localization and mapping of indoor mobile robot

Xingdong Liu, Xiao Luo, Xinliang Zhong

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

Abstract

Simultaneous localization and mapping (SLAM) is the key technology to fulfill mobile robot obstacle avoidance and autonomous navigation. As cameras such as binocular cameras or RGB-D cameras exist wide-angle limitations, the use of such sensors prone to map mismatches and localization errors. In order to solve the aforementioned problems, 2D laser radar and odometer are used as the core sensor to design an experimental system for indoor SLAM, which is configured on a mobile robot to examine the effect of indoor SLAM. Through the Rao-Blackwellized [1] particle filter algorithm, the data of laser radar and odometer are fused with real-time processing, which realizes the construction of map as well as localization and navigation of the mobile robot in the unknown environment. Experiments on simulation and physical verification were carried out with open source robot operating system (ROS). The simulation and experimental results confirm the feasibility and practicability of the platform.

Original languageEnglish
Article number012099
JournalJournal of Physics: Conference Series
Volume1074
Issue number1
DOIs
Publication statusPublished - 30 Aug 2018
EventInternational Conference on Mechanical, Electric and Industrial Engineering, MEIE 2018 - Hangzhou, China
Duration: 12 May 201814 May 2018

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