  This paper presents a hierarchical segment-based optimization method for
Simultaneous Localization and Mapping (SLAM) system. First we propose a
reliable trajectory segmentation method that can be used to increase efficiency
in the back-end optimization. Then we propose a buffer mechanism for the first
time to improve the robustness of the segmentation. During the optimization, we
use global information to optimize the frames with large error, and
interpolation instead of optimization to update well-estimated frames to
hierarchically allocate the amount of computation according to error of each
frame. Comparative experiments on the benchmark show that our method greatly
improves the efficiency of optimization with almost no drop in accuracy, and
outperforms existing high-efficiency optimization method by a large margin.
