面向自主靠离泊环境的USV激光SLAM方法  

USV lidar SLAM method for autonomous berthing and unberthing environment

作　　者：刘华康 何佳洲[1] 王景石 蔡庆 滕欣进 LIU Huakang;HE Jiazhou;WANG Jingshi;CAI Qing;TENG Xinjin(High Tech Department,Jiangsu Automation Research Institute,Lianyungang 222061,China;CSSC Beijing Intelligent Equipment Technology Co.,Ltd.,Beijing 102600,China)

机构地区：[1]江苏自动化研究所高新技术部,江苏连云港222061 [2]中船(北京)智能装备科技有限公司,北京102600

出　　处：《舰船科学技术》2025年第3期117-122,共6页Ship Science and Technology

基　　金：国防科工局预研项目(JCKY2021206B015)。

摘　　要：在自主靠离泊环境中,水面无人艇使用传统激光同步定位与建图算法面临许多挑战,如水面高动态变化、水波干扰和局部极值问题等。针对这些问题,本文提出一种基于改进LIO-SAM(Lidar Inertial Odometry via Smoothing and Mapping)的USV(Unmanned Surface Vehicle)激光SLAM(Simultaneous Localization and Mapping)算法。首先,通过优化惯性测量单元预积分过程,在保持算法水面动态环境下精度的同时,降低了计算负担;其次,引入了一种基于复合滤波的水波干扰抑制方法,降低了水波对激光SLAM的影响;最后,采用了一种改进的图优化方法,有效解决了局部极值问题。实验结果表明,所提出的算法在USV的自主靠离泊环境中具有较高的定位精度和稳定性。In the autonomous berthing and unberthing environment,the unmanned surface vehicle(USV)using the tra-ditional simultaneous localization and mapping(SLAM)algorithm faces many challenges,such as high dynamic changes of water surface,water wave interference and local extremum problems.To solve these problems,this paper proposes a USV lidar SLAM algorithm based on improved LIO-SAM(Lidar Inertial Odometry via Smoothing and Mapping).Firstly,by optimizing the pre integration process of inertial measurement unit(IMU),the computational burden is reduced while main-taining the accuracy of the algorithm in the dynamic environment of water surface;Secondly,a water wave interference sup-pression method based on composite filtering is introduced to reduce the influence of water wave on lidar SLAM;Finally,an improved graph optimization method is used to effectively solve the local extremum problem.Experimental results show that the proposed algorithm has high positioning accuracy and stability in the autonomous berthing and unberthing environment ofUSV.

关 键 词：无人艇 同步定位与建图 自主靠离泊 水波干扰 

分 类 号：U665.22[交通运输工程—船舶及航道工程]