A tight coupling mapping method to integrate the ESKF, g2o, and point cloud alignment

High-precision point cloud maps have drawn increasing attention due to their wide range of applications. In recent decades, point cloud maps are normally generated by simultaneous localization and mapping (SLAM) methods, which favor real-time performance over high precision. These methods generally focus on trajectory accuracy resulting in the unclearness of map accuracy. Therefore, to build a high-precision point cloud map and evaluate the mapping performance directly, this study proposes a tight coupling mapping method that integrates the error-state Kalman filter (ESKF), the general framework for graph optimization (g2o), and the point cloud alignment. An ESKF and a g2o are both used to improve the precision of the mapping process. Also, experiments based on a mobile mapping backpack prototype are conducted to verify the proposed method. Targets in the environment and a high-precision reference point cloud map are used to directly evaluate the map performance. The results indicate that the generated point cloud map is sufficiently precise and can reach the centimeter level.

Subjects

Mapping

ESKF

Point Cloud Alignment...

LiDAR

A tight coupling mapping method to integrate the ESKF, g2o, and point cloud alignment

Availability at HKSYU Library