In this paper, we propose a novel LiDAR(-inertial) odometry and mapping framework to achieve the goal of simultaneous localization and meshing in real-time. This proposed framework termed ImMesh comprises four tightly-coupled modules: receiver, localization, meshing, and broadcaster. The localization module utilizes the prepossessed sensor data from the receiver, estimates the sensor pose online by registering LiDAR scans to maps, and dynamically grows the map. Then, our meshing module takes the registered LiDAR scan for incrementally reconstructing the triangle mesh on the fly. Finally, the real-time odometry, map, and mesh are published via our broadcaster. The key contribution of this work is the meshing module, which represents a scene by an efficient hierarchical voxels structure, performs fast finding of voxels observed by new scans, and reconstructs triangle facets in each voxel in an incremental manner. This voxel-wise meshing operation is delicately designed for the purpose of efficiency; it first performs a dimension reduction by projecting 3D points to a 2D local plane contained in the voxel, and then executes the meshing operation with pull, commit and push steps for incremental reconstruction of triangle facets. To the best of our knowledge, this is the first work in literature that can reconstruct online the triangle mesh of large-scale scenes, just relying on a standard CPU without GPU acceleration. To share our findings and make contributions to the community, we make our code publicly available on our GitHub: https://github.com/hku-mars/ImMesh.

翻译：在本文中, 我们提出一个新的 LiDAR (- 内线性) odology 和 映射框架, 以实现同时本地化和实时网格的目标。 这个名为 ImMesh 的拟议框架由四个紧密的组合模块组成: 接收器、 本地化、 网目和广播器。 本地化模块使用接收器预存的传感器数据, 通过注册 LiDAR 扫描地图来估计传感器在网络上出现, 并动态地增长地图 。 然后, 我们的网状图像模块将注册的LiDAR 扫描用于逐渐地重建三角网格网格。 最后, 实时快速的odography、 地图和网状网状图集由高效的等级 vishmus 结构显示一个场景, 通过新的扫描快速地查找 voxel, 并以渐进的方式重建每个 voxel 的三角形图层。 这个软盘图像操作非常微妙, 是为了提高效率而设计的 ; 它首先通过不通过我们的广播机 直径 将 3D rodeal rodudeal main distration madeal destrual destration main mail mab the the the preal destreal destruteal shales max max max maild the the the sreal list shareal shalm shales mas mas mas mas las dreal shareal dreal list list maildaldal maildal list sharealdals max mas max max max max libals mas shals libal mas mas mas.