Mobile robot localization and mapping based on mixed model - 文章详情页

作者：

Jia, Songmin (Jia, Songmin.) (学者：贾松敏) | Yang, Hao (Yang, Hao.) | Li, Xiuzhi (Li, Xiuzhi.) | Cui, Wei (Cui, Wei.)

收录：

EI Scopus

摘要：

This　paper　presents　a　new　method　of　localization　and　map　building　of　mobile　robot　based　on　mixed　map　model　using　LRF　(Laser　Range　Finder).　The　mixed　model　composed　of　occupancy　grids　and　line　character　maps　is　utilized　to　represent　the　environment　map.　Firstly,　the　LRF　models　and　Bayes　rules　are　used　to　construct　a　local　occupancy　grid　map.　Then,　we　extract　obstacles　points　to　get　a　precise　geometry　character　map　through　region　partitioning,　line　segment　extracting　and　fitting　to　construct　the　global　map.　Meanwhile,　EKF　(Extended　Kalman　Filter)　through　state　prediction,　observation　prediction　and　estimation　phase,　is　utilized　to　estimate　the　robot　pose　and　correct　the　map　model.　What＇s　more,　the　operator　can　use　interactive　GUI　(Graphical　User　Interface)　to　control　the　robot　conveniently.　The　simulation　results　and　the　real　experimental　results　indicate　the　feasibility　and　validity　of　this　approach.　©　2010　IEEE.

关键词：

Extended Kalman filters Robot applications Range finders Mobile robots Graphical user interfaces

作者机构：

[ 1 ] [Jia, Songmin]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 2 ] [Yang, Hao]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 3 ] [Li, Xiuzhi]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 4 ] [Cui, Wei]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China

通讯作者信息：

电子邮件地址：

jsm@bjut.edu.cn

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