Modern laser SLAM (simultaneous localization and mapping) and structure from motion algorithms face the problem of processing redundant data. Even if a sensor does not move, it still continues to capture scans that should be processed. This paper presents the novel filter that allows dropping 2D scans that bring no new information to the system. Experiments on MIT and TUM datasets show that it is possible to drop more than half of the scans. Moreover the paper describes the formulas that enable filter adaptation to a particular robot with known speed and characteristics of lidar. In addition, the indoor corridor detector is introduced that also can be applied to any specific shape of a corridor and sensor.

来自运动算法的现代激光SLAM（同时定位和映射）和结构面临着处理冗余数据的问题。即使传感器不移动，它仍会继续捕获应处理的扫描。本文介绍了一种新颖的过滤器，该过滤器允许丢弃2D扫描，从而不会给系统带来任何新信息。MIT和TUM数据集上的实验表明，有可能丢弃一半以上的扫描。此外，本文还描述了公式，该公式使过滤器可以适应具有已知速度和激光雷达特性的特定机器人。另外，引入了室内走廊检测器，该检测器也可以应用于走廊和传感器的任何特定形状。