Landmark matching in a varying environment

A system for landmark tracking by a template matching approach is described. Route following based on landmarks may require many models to cover all different situations, so a genetic algorithm learning technique is used to adapt modelling parameters to environmental conditions (lighting, shadows, reflexes, etc.) during the tracking. In addition, the mobile robot self-localization is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence analysis in the 3-D position estimation. The experimental results show that the tracking robustness is improved when the adaptive template matching is used for landmark tracking.