Global localization based on corner point

Map matching is a type of popular localization approaches for mobile robot autonomous navigation in indoor environment. Global localization is to find the best correspondence between current local map and the global map. Local map and global map are represented with corner points that are sorted in counterclockwise. The relative position relation of corner points is computed in local and global map and used to search matched pairs. Map matching based on ordinal map improves the searching efficiency. Map matching based on relative position relation avoids frequent coordinates transformation. All these techniques have been implemented on our mobile robot ATRVII equipped with 2D laser range scanner SICK.

[1]  Qingxiang Wu,et al.  Rough computational methods on reducing cost of computation in Markov localization for mobile robots , 2002, Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527).

[2]  Wolfram Burgard,et al.  Monte Carlo localization for mobile robots , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[3]  Wolfram Burgard,et al.  Integrating global position estimation and position tracking for mobile robots: the dynamic Markov localization approach , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[4]  Ingemar J. Cox,et al.  Blanche-an experiment in guidance and navigation of an autonomous robot vehicle , 1991, IEEE Trans. Robotics Autom..

[5]  Hugh F. Durrant-Whyte,et al.  Localization system for a high-speed land vehicle , 1998, Other Conferences.

[6]  Jun Ota,et al.  Uniform Monte Carlo localization - fast and robust self-localization method for mobile robots , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[7]  Henrik I. Christensen,et al.  Laser based pose tracking , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[8]  Joachim Weber,et al.  APR - Global Scan Matching Using Anchor Point Relationships , 2000 .

[9]  J.-S. Gutmann,et al.  AMOS: comparison of scan matching approaches for self-localization in indoor environments , 1996, Proceedings of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT '96).

[10]  A.-J. Baerveldt,et al.  Localization in changing environments by matching laser range scans , 1999, 1999 Third European Workshop on Advanced Mobile Robots (Eurobot'99). Proceedings (Cat. No.99EX355).