Tracking and data association
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Experiences with an interactive museum tour-guide robot
Artificial Intelligence - Special issue on applications of artificial intelligence
Vision-Based Vehicle Guidance
Navigating Mobile Robots: Systems and Techniques
Navigating Mobile Robots: Systems and Techniques
Vision and Navigation: The Carnegie Mellon Navlab
Vision and Navigation: The Carnegie Mellon Navlab
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In autonomous indoor navigation some number of localizations and orientations of the vehicle can be learned in advance. No artificial landmarks are required to exist. We describe and compare the detection of several global features of color images (sensor data). This constitutes the measurement process in a self-localization approach that is based on Bayes filtering of a Markov environment – the posterior probability density over possible discrete robot locations (the belief) is recursively computed. The approach was tested to provide robust results under varying scene brightness conditions and small measurement errors.