  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
thepaper 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.
