A Low-cost and Robust Mapping and Relocalization Method Base on Lidar Inertial Odometry

Abstract

LOAM (lidar odometry and mapping) plays an important role in the field of mobile robot and relocalization is essential for navigation. In this paper, we propose a system of LOAM and real-time relocalization based on a low cost lidar with small FoV (field of view) and IMU. Due to the lack of features in lidar with small FoV, the LOAM algorithm is easy to lose the target and mismatch when turning. We settle this problem by integrating lidar with IMU. To accelerate the matching process in relocalization, our relocalization algorithm is based on the feature points map, not the full map. Finally we demonstrate our system to be accurate and robust by experiments in our school.