Abstract Building 3D maps of various terrains is a necessary approach to gain environmental information for mobile robots when they are exploring in unknown territories. In this paper, we propose a method to construct a point cloud map with laser-measured data as the robot moves around. A terrain-adaptive density mapping technique is used to balance the demands of small data size and high terrain accuracy by utilizing the local curvatures as the simplification criteria. The adaptive density mapping technique is further integrated within the map merging framework to improve the matching speed and accuracy. Indoor and outdoor experiments are proceeded, which verifies the effects of using terrain-adaptive density point cloud on controlling the map size and decreasing the map alignment error.

中文翻译：

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使用移动 3D 激光扫描仪将地图与地形自适应密度合并

摘要 构建各种地形的 3D 地图是移动机器人在未知领域探索时获取环境信息的必要途径。在本文中，我们提出了一种在机器人四处移动时使用激光测量数据构建点云图的方法。地形自适应密度映射技术通过利用局部曲率作为简化标准来平衡小数据量和高地形精度的需求。自适应密度映射技术进一步集成在地图合并框架中，以提高匹配速度和准确性。进行了室内和室外实验，验证了使用地形自适应密度点云控制地图大小和减少地图对齐误差的效果。