Scale Estimation of Monocular Camera SLAM using a 2D Lidar

Abstract

SLAM using a monocular camera has the problem that scale cannot be uniquely estimated, and scale drift occurs. This study uses 2D Lidar scan data to improve scale drift and enable scale estimation. Specifically, we improve scale estimation and scale drift by averaging the ratio of distances between the 3D point cloud reconstructed by monocular SLAM and the 2D Lidar point cloud by mapping the data based on the viewing direction. The accuracy is further improved by following the concept of M-estimation