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In this paper the supervisory control of the Person-Following Robot Platform   is presented. The main part of the high level control loop of mobile robot   platform is a real-time robust algorithm for human detection and tracking.   The main goal was to enable mobile robot platform to recognize the person in   indoor environment, and to localize it with accuracy high enough to allow   adequate human-robot interaction. The developed computationally intelligent   control algorithm enables robust and reliable human tracking by mobile robot   platform. The core of the recognition methods proposed is genetic   optimization of threshold segmentation and classification of detected regions   of interests in every frame acquired by thermal vision camera. The support   vector machine classifier determines whether the segmented object is human or   not based on features extracted from the processed thermal image   independently from current light conditions and in situations where no skin   color is visible. Variation in temperature across same objects, air flow with   different temperature gradients, person overlap while crossing each other and   reflections, put challenges in thermal imaging and will have to be handled   intelligently in order to obtain the efficient performance from motion   tracking system. [Projekat Ministarstva nauke Republike Srbije, br. TR35005

Intelligent optimal control of thermal vision-based Person-Following Robot Platform