  SLAM technology has recently seen many successes and attracted the attention
of high-technological companies. However, how to unify the interface of
existing or emerging algorithms, and effectively perform benchmark about the
speed, robustness and portability are still problems. In this paper, we propose
a novel SLAM platform named GSLAM, which not only provides evaluation
functionality, but also supplies useful toolkit for researchers to quickly
develop their own SLAM systems. The core contribution of GSLAM is an universal,
cross-platform and full open-source SLAM interface for both research and
commercial usage, which is aimed to handle interactions with input dataset,
SLAM implementation, visualization and applications in an unified framework.
Through this platform, users can implement their own functions for better
performance with plugin form and further boost the application to practical
usage of the SLAM.
