论文标题
检测无效的地图合并终身大满贯
Detecting Invalid Map Merges in Lifelong SLAM
论文作者
论文摘要
对于终身大满贯，必须处理临时定位失败，例如绑架引起的。我们通过启动新的地图并在重新定位成功后立即将其与先前的地图合并来实现这一目标。由于重新定位方法是容易造成的，因此可能会发生这种合并无效，例如，由于知觉的混叠。为了解决这个问题，我们提出了检测和撤消无效合并的方法。这些方法将传入的扫描与以前合并到当前地图中的扫描，并考虑它们彼此之间的同意程度。对我们方法的评估是使用由多个平面和办公环境以及公共麻省理工学院Stata Center数据集组成的数据集进行的。我们表明，基于变更检测算法和Gridmaps比较的方法在这两个环境中都表现良好，并且可以通过合理的计算成本实时运行。
For Lifelong SLAM, one has to deal with temporary localization failures, e.g., induced by kidnapping. We achieve this by starting a new map and merging it with the previous map as soon as relocalization succeeds. Since relocalization methods are fallible, it can happen that such a merge is invalid, e.g., due to perceptual aliasing. To address this issue, we propose methods to detect and undo invalid merges. These methods compare incoming scans with scans that were previously merged into the current map and consider how well they agree with each other. Evaluation of our methods takes place using a dataset that consists of multiple flat and office environments, as well as the public MIT Stata Center dataset. We show that methods based on a change detection algorithm and on comparison of gridmaps perform well in both environments and can be run in real-time with a reasonable computational cost.
