Scan matching based on CLS relationships

Position estimation based on scan matching is a type of popular approaches for mobile robot localization in indoor office-like environments. Global scan matching and local scan matching are two basic position estimation problems. Global scan matching is subject to global localization for mobile robo...

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Published inIEEE International Conference on Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 Vol. 1; pp. 99 - 104 vol.1
Main Authors Xu Zezhong, Liu Jilin, Xiang Zhiyu
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
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ISBN078037925X
9780780379251
DOI10.1109/RISSP.2003.1285556

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Abstract Position estimation based on scan matching is a type of popular approaches for mobile robot localization in indoor office-like environments. Global scan matching and local scan matching are two basic position estimation problems. Global scan matching is subject to global localization for mobile robot and local scan matching is used to deal with tracking mobile robot position over time. Global localization based on scan matching is represented in this paper. A global map is built to represent whole environment feature and a local map is built to represent current range scan. Global map and local map consist of a lot of line segments. Complete line segment that represents a complete environment object is singled out and used to match between local map and global map. Line segments are sorted counterclockwise in two maps. This type of ordinal map improves the searching efficiency of matching and localization algorithm is timesaving. In addition, matching between current range scan and global map is based on relative position relationships of line segments in local and global map. Global localization based on relative position relationship avoids frequent coordinates transformation and lowers computational cost. All these techniques have been implemented on our mobile robot ATRVII equipped with 2D laser range scanner SICK.
AbstractList Position estimation based on scan matching is a type of popular approaches for mobile robot localization in indoor office-like environments. Global scan matching and local scan matching are two basic position estimation problems. Global scan matching is subject to global localization for mobile robot and local scan matching is used to deal with tracking mobile robot position over time. Global localization based on scan matching is represented in this paper. A global map is built to represent whole environment feature and a local map is built to represent current range scan. Global map and local map consist of a lot of line segments. Complete line segment that represents a complete environment object is singled out and used to match between local map and global map. Line segments are sorted counterclockwise in two maps. This type of ordinal map improves the searching efficiency of matching and localization algorithm is timesaving. In addition, matching between current range scan and global map is based on relative position relationships of line segments in local and global map. Global localization based on relative position relationship avoids frequent coordinates transformation and lowers computational cost. All these techniques have been implemented on our mobile robot ATRVII equipped with 2D laser range scanner SICK.
Author Xu Zezhong
Liu Jilin
Xiang Zhiyu
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  organization: Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China
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  surname: Liu Jilin
  fullname: Liu Jilin
  organization: Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China
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  surname: Xiang Zhiyu
  fullname: Xiang Zhiyu
  organization: Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China
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Snippet Position estimation based on scan matching is a type of popular approaches for mobile robot localization in indoor office-like environments. Global scan...
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StartPage 99
SubjectTerms Computational efficiency
Distributed computing
Filtering
Mobile computing
Mobile robots
Navigation
Orbital robotics
Robot kinematics
Robot sensing systems
State-space methods
Title Scan matching based on CLS relationships
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