Abstract: This paper proposes a three-dimensional mapping system for in-hold environments oriented toward cleaning operations, to address the operational characteristics of bulk carrier holds—namely enclosed spaces, weak geometric features, and the continuous removal of bulk materials during cleaning, which leads to a gradual decrease in pile height and constantly changing surface morphology—aiming to achieve a stable and updatable 3D representation of the hold environment. A multi-LiDAR and inertial measurement unit (IMU) collaborative 3D mapping system is built on a hold-cleaning machine platform. Spatiotemporal consistency across sensors is ensured through time synchronization and extrinsic calibration. Motion compensation of LiDAR point clouds is performed using IMU preintegration, and pose estimation is carried out via a tightly coupled LiDAR and IMU odometry method. Combined with sliding-window local mapping and an incremental voxel-based map representation, the system enables real-time construction and continuous updating of the in-hold 3D map. Verification through multiple field experiments shows that the proposed system can robustly estimate the pose of the hold-cleaning machine under feature-sparse and highly dynamic operating conditions, while producing structurally complete and continuously updated 3D point cloud maps. The generated maps effectively capture key structures, including hold walls, the hold floor, and bulk material surfaces, thereby meeting the requirements for remote visualization and operational awareness. The proposed system is well suited to bulk carrier hold-cleaning scenarios and provides a reliable foundation for three-dimensional environmental perception in autonomous hold-cleaning operations.

Key words: bulk carrier hold, 3D mapping, simultaneous localization and mapping (SLAM), light detection and ranging (LiDAR), multi-sensor fusion

摘要： 针对散货船船舱空间封闭、几何特征弱,以及清舱过程中散料被逐步清除导致料堆高度持续下降、表面形态不断变化的作业特点,该文研究了一种面向清舱作业的船舱内三维建图系统,实现对舱内环境稳定且可动态更新的表示。文章首先以清舱机为载体,构建多激光雷达与惯性测量单元（inertial measurement unit,IMU）协同感知的三维建图系统,通过时间同步与外参标定实现多源传感器的时空一致表达;在此基础上,借助IMU预积分完成点云运动补偿,利用激光雷达与IMU紧耦合里程计开展位姿估计,并结合滑动窗口局部建图与增量体素地图表示,实现舱内三维地图的实时构建与更新。经多项实地试验验证,结果表明该系统能够在弱特征、高动态作业条件下稳定完成清舱设备位姿估计,并构建结构完整、持续更新的舱内三维点云地图;所生成地图能够有效反映舱壁、舱底及散料表面等关键结构特征,满足远程可视化与作业感知需求。该系统适用于散货船船舱清舱作业场景,可为无人清舱作业提供可靠的三维环境感知基础。

关键词: 散货船, 三维建图, 同步定位与建图, 激光雷达, 多传感器融合