Translational Motion Estimation Using Kinect

Abstract

Study on robot navigation has been progressing significantly. However, research of autonomous navigation is still lacking in environments with changing layout. For supporting robot navigation system, rotational and translational motion estimation need to be improved. Low cost sensor such as Kinect can be used as alternative to laser to percept changing in the vicinity of robot. There is still problem in developing motion estimation using Kinect. Narrowness in the sensor field of view limits its ability to track robot motion. This problem emerges specially in translational motion estimation. This paper aims to develop a simple approach based on RGB-D data for translational motion estimation of a Kinect sensor. RGB-D data consist of RGB and Depth images. In previous research, camera was positioned in the direction of longitudinal translational motion. This paper differs from previous works in terms of sensor setting that is placed in the direction of lateral translation movements. Point features are matched between pairs of RGB frame to get interesting pixels. Depth image provides distance information for these pixels in synchronization with feature tracking process. Law of cosines is then applied to these depth pixels to get position translation. Results show that our approach have decreased RMSE to 0.0382 meter better than previous works. In the future research, this translational motion estimation system will be implemented in mobile robot system to support navigation function.