Methods For Simultaneous Self-Localization And Mapping For Depth Cameras

Abstract

This work deals with the extension of the existing implementation of RGBD Visual SLAM with additional data source from wheel odometry of robot’s chassis, on which RGBD sensor is located. Each of these two position estimation methods has a different character measurement uncertainty. By combining these methods together we could be able to suppress the disadvantages of both approaches, and in the result we would be able to create more accurate model of the robot’s environment, which was unknown at the beginning of the measurement. Also accuracy of position estimation in created model can be improved.