面向港口环境精细感知的无人船多传感器融合SLAM系统

Multi-Sensor Fusion SLAM System of an Unmanned Surface Vehicle for Fine Sensing in Port Environment

针对港口环境高精度感知需求,综合考虑影响同时定位与建图(SLAM)精度的港口环境因素,提出基于多传感器融合的激光SLAM环境感知方案。通过分析多种传感器对港口SLAM环境感知的影响,引入惯性测量传感器弥补激光SLAM输出频率低和剧烈运动位姿估计不准确等缺陷,采用卫星定位系统信息进行高程数据约束,处理船舶运动特性导致的垂荡累计漂移。从应用需求出发,对传感器进行选型和布置优化,搭建基于无人船的港口环境多传感器融合SLAM系统。结果表明,提出的港口环境高精度点云地图获取方案能在典型港口场景下准确实时建图,为水面精细SLAM提供技术支持。

In response to the demands for high-precision port environment perception,a Lidar simultaneous localization and mapping(SLAM)environment perception scheme based on multi-sensor fusion is proposed by comprehensively considering the port environment factors that affect the accuracy of SLAM.By analyzing the impact of various sensors on the environment perception of port SLAM,inertial measurement sensors are introduced to compensate for the shortcomings of low output frequency of Lidar SLAM and inaccurate pose estimation under intense motion.Introduce elevation data constraints based on satellite positioning system information to handle accumulated heave drift caused by ship motion characteristics.Starting from application requirements,sensor selection and layout optimization are carried out to build a multi-sensor fusion SLAM system for port environment based on unmanned surface vehicle.The results indicate that the proposed high-precision point cloud map acquisition scheme for port environment can accurately and real-time construct maps in typical port scenarios,providing technical support for fine SLAM of water surface.