Fast Pose Tracking Based on Ranked 3D Planar Patch Correspondences

A fast robot pose tracking algorithm based on planar segments extracted from range images is presented. A range image obtained from a 3D sensor is transformed to a 2.5D triangle mesh from which planar segments are extracted. Using information provided by each planar segment based on its size and orientation, a directed search hypothesis generation algorithm using a tree structure is presented. The presented approach is experimentally evaluated using 3D data obtained by a Kinect sensor mounted on a mobile robot. Results indicate that the proposed method is much faster than similar previously proposed methods.