Real-time slam based on Hybrid Odometry and LDPDs (Local differential Probability Distances)

This paper presents a new type of SLAM for indoor and outdoor environments. This method solves only the simplest localization problem, position tracking, and does not use the mapping information in localization. The proposed SLAM uses hybrid odometry for the localization. Mapping is based on LDPDs (local differential probability distances) and accumulated 3D dense frames.