A method for discrete self-localization using image analysis

A method for discrete self-localization of an autonomous mobile system was proposed. One of its many possible implementations was designed, that uses a camera subsystem, which delivers sensor information about the environment reduced to an n-elementary measurement vector. Three different algorithms of image analysis were proposed and implemented. The self-localization approach with three different image sub-systems was tested by computer simulations on different natural and synthetic scenes.

[1]  W. Burgard,et al.  Markov Localization for Mobile Robots in Dynamic Environments , 1999, J. Artif. Intell. Res..

[2]  Wolfram Burgard,et al.  Experiences with an Interactive Museum Tour-Guide Robot , 1999, Artif. Intell..

[3]  Markus Maurer,et al.  A compact vision system for road vehicle guidance , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[4]  Takeo Kanade,et al.  Vision and Navigation for the Carnegie-Mellon Navlab , 1987 .

[5]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[6]  I. Masaki,et al.  Vision-based vehicle guidance , 1992, Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation.

[7]  Włodzimierz Kasprzak,et al.  Adaptive computation methods in digital image sequence analysis , 2000 .

[8]  Martial Hebert,et al.  Vision and navigation for the Carnegie-Mellon Navlab , 1988 .