U-LOAM: A Real-Time 3D Lidar SLAM System for Water-Surface Scene Applications

Abstract

Simultaneous localization and mapping (SLAM) is a crucial technology for autonomous navigation of unmanned surface vehicles (USVs). Whereas, due to the existence of sparse feature points and constant vibration interference, the accuracy of SLAM system positioning and mapping will be affected in water-surface scene applications. To tackle this problem, a tightly coupled Lidar and inertial measurement unit (IMU) SLAM system, which is suitable for water-surface scene applications, is constructed. Firstly, the integration of IMU output is used as a correction basis to eliminate Lidar point cloud distortion. Secondly, according to the IMU pre-integration model, a tightly coupled algorithm of Lidar and IMU is developed. Thirdly, on the basis of keyframes, a sliding window mapping algorithm is proposed to reduce system computation. Fourthly, a loop optimization module based on the factor graph is added to reduce cumulative errors. Finally, some comparative experiments are implemented to demonstrate the effective of the proposed methods in unknown water-surface environments.