UFOMap: An Efficient Probabilistic 3D Mapping Framework That Embraces the Unknown
UFOMap: An Efficient Probabilistic 3D Mapping Framework That Embraces the Unknown
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DOI：
10.1109/lra.2020.3013861
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发表时间：
2020-10-01
影响因子：
5.2
通讯作者：
Jensfelt, Patric
中科院分区：
文献类型：
--
作者：
Duberg, Daniel;Jensfelt, Patric
3D模型是许多机器人应用的重要组成部分。在环境先验未知或仅部分环境已知的应用中，重要的是3D模型可以有效地处理未知空间。路径规划、探索和重建都属于这一类。在这封信中，我们提出了一个扩展到UFOMap，我们称之为UFOMap。UFOMap使用地图中所有三个状态的显式表示，即，未知的，自由的，被占领的。令人惊讶的是，这给出了一种更有效的存储器表示。我们提供的方法，允许显着更快的插入到八叉树。此外，UFOMap支持快速查询占用状态的基础上使用所谓的指标和位置的基础上利用八叉树结构和包围体。这使得实时彩色八叉树映射在高分辨率（低于1厘米）。UFOMap是一个C++库，可以独立使用，也可以集成到ROS中。
3D models are an essential part of many robotic applications. In applications where the environment is unknown a-priori, or where only a part of the environment is known, it is important that the 3D model can handle the unknown space efficiently. Path planning, exploration, and reconstruction all fall into this category. In this letter we present an extension to OctoMap which we call UFOMap. UFOMap uses an explicit representation of all three states in the map, i.e., unknown, free, and occupied. This gives, surprisingly, a more memory efficient representation. We provide methods that allow for significantly faster insertions into the octree. Furthermore, UFOMap supports fast queries based on occupancy state using so called indicators and based on location by exploiting the octree structure and bounding volumes. This enables real-time colored octree mapping at high resolution (below 1 cm). UFOMap is contributed as a C++ library that can be used standalone but is also integrated into ROS.