  In this paper we consider a hierarchical pose graph optimization (HPGO) for
Simultaneous Localization and Mapping (SLAM). We propose a fast incremental
procedure for building hierarchy levels in pose graphs. We study the properties
of this procedure and show that our solution delivers high execution speed,
high reduction rate and good flexibility. We propose a way to do partial
hierarchical optimization and compare it to other optimization modes. We show
that given a comparatively large amount of poses, partial HPGO gives a 10x
speed up comparing to the original optimization, not sacrificing the quality.
