This paper addresses position estimation of a micro-rover mobile robot (called the “daughter”) as a larger robot (the “mother”) tracks it through large spaces with unstructured lighting. Position estimation is necessary for localization, where the mother extracts the relative position of the daughter for mapping purposes, and for cooperative navigation, where the mother controls the daughter in real-time. The approach taken is to employ the Spherical Coordinate Transform color segmenter developed for medical applications as a low computational and hardware cost solution. Data was collected from 50 images taken in five types of lighting: fluorescent, tungsten, daylight lamp, natural daylight indoors and outdoors. The results show that average pixel error was 1.5, with an average error in distance estimation of 6.3 cm. The size of the error did not vary greatly with the type of lighting. The segmentation and distance tracking have also been implemented as a real-time tracking system. Using this system, the mother robot is able to autonomously control the micro-rover and display a map of the daughter's path in real-time using only a Pentium class processor and no specialized hardware.
color segmentationcooperative navigationvisual trackingmobile robots