Hierarchical SLAM:: Real-time accurate mapping of large environments
Hierarchical SLAM:: Real-time accurate mapping of large environments
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DOI：
10.1109/tro.2005.844673
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发表时间：
2005-08-01
影响因子：
7.8
通讯作者：
Tardós, JD
中科院分区：
文献类型：
--
作者：
Estrada, C;Neira, J;Tardós, JD
在本文中，我们提出了一种分层映射方法，使我们能够实时获得大型环境的准确度量地图。较低(或局部)映射级别由一组确保统计独立的局部映射组成。较高(或全局)级别是一个邻接图，其圆弧用局部地图之间的相对位置进行标记。在相对随机地图中，对这些相对位置的估计维持在该水平。我们提出了一种接近最优的环路关闭方法，该方法在保持局部级独立性的同时，以与环路大小成线性的计算代价在全局级强制一致性。通过对我校Ada Byron大楼的测绘实验，验证了该方法的有效性和准确性。我们还利用模拟分析了我们的方法对于较大回路的精度和收敛。
In this paper, we present a hierarchical mapping method that allows us to obtain accurate metric maps of large environments in real time. The lower (or local) map level is composed of a set of local maps that are guaranteed to be statistically independent. The upper (or global) level is an adjacency graph whose arcs are labeled with the relative location between local maps. An estimation of these relative locations is maintained at this level in a relative stochastic map. We propose a close to optimal loop closing method that, while maintaining independence at the local level, imposes consistency at the global level at a computational cost that is linear with the size of the loop. Experimental results demonstrate the efficiency and precision of the proposed method by mapping the Ada Byron building at our campus. We also analyze, using simulations, the precision and convergence of our method for larger loops.