用自适应分辨率网格实时构建紧凑3D地图，精度更高、体积更小。
PlanarMesh: Building Compact 3D Meshes from LiDAR using Incremental Adaptive Resolution Reconstruction
- 基于平面与网格融合的新表示，动态调整细节密度
- 64线激光雷达下达2帧/秒，文件大小比原始数据小10倍
- 适合需要高效实时3D建图的机器人或自动驾驶场景
构建在线3D LiDAR映射系统，在保持高细节的同时实现计算高效极具挑战。本文提出PlanarMesh，一种增量式、基于网格的LiDAR重建系统，通过自适应调整网格分辨率，实现实时的紧凑且详细的表面重建。该方法引入新型表示——平面网格（planar-mesh），结合平面建模与网格化，同时捕捉大尺度表面与精细几何结构。其可增量更新，综合考虑局部曲率与传感器测量的空域信息。采用多线程架构与包围体层次结构（BVH）实现高效存储与快速查询，保障实时性能。实验表明，本方法在重建精度上达到或超越当前最优技术——包括截断有符号距离函数、占用映射和体素网格法，输出文件尺寸仅为原始输入的1/10，且远小于其他网格方法的1/5，同时维持约2帧/秒的实时性能（针对64线传感器）。
原文摘要 · Abstract (English)
Building an online 3D LiDAR mapping system that produces a detailed surface reconstruction while remaining computationally efficient is a challenging task. In this paper, we present PlanarMesh, a novel incremental, mesh-based LiDAR reconstruction system that adaptively adjusts mesh resolution to achieve compact, detailed reconstructions in real-time. It introduces a new representation, planar-mesh, which combines plane modeling and meshing to capture both large surfaces and detailed geometry. The planar-mesh can be incrementally updated considering both local surface curvature and free-space information from sensor measurements. We employ a multi-threaded architecture with a Bounding Volume Hierarchy (BVH) for efficient data storage and fast search operations, enabling real-time performance. Experimental results show that our method achieves reconstruction accuracy on par with, or exceeding, state-of-the-art techniques-including truncated signed distance functions, occupancy mapping, and voxel-based meshing-while producing smaller output file sizes (10 times smaller than raw input and more than 5 times smaller than mesh-based methods) and maintaining real-time performance (around 2 Hz for a 64-beam sensor).
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