Boosting support vector machines for RGB-D based terrain classification

This paper deals with the terrain classification problem for an autonomous mobile robot. The robot is designed to operate in an outdoor environment. The classifier integrates data from RGB camera and 2D laser scanner. The camera provides information about visual appearance of the objects in front of the robot. The laser scanner provides data about distance to the objects and their ability to reflect infrared beam. In this paper we present the method which create terrain segments and classifies them using joint application of Support Vector Machine (SVM) classifier and AdaBoost algorithm. The classifica- tion results of the experimental verification are provided in the paper.