J Shanghai Jiaotong Univ Sci

Journal of Shanghai Jiaotong University(Science) >

2020 , Vol. 25 >Issue 5: 650 - 658

DOI: https://doi.org/10.1007/s12204-020-2201-4

Low Data Overlap Rate Graph-Based SLAM with Distributed Submap Strategy

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  • (1. Key laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200444, China;
    2. Institute of System Integration, Shanghai Sansi Electronic Engineering Co., Ltd., Shanghai 201100, China)

Online published: 2020-09-11

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Abstract

 Simultaneous localization and mapping (SLAM) is widely used in many robot applications to acquire
the unknown environment’s map and the robot’s location. Graph-based SLAM is demonstrated to be effective in
large-scale scenarios, and it intuitively performs the SLAM as a pose graph. But because of the high data overlap
rate, traditional graph-based SLAM is not efficient in some respects, such as real time performance and memory
usage. To reduce data overlap rate, a graph-based SLAM with distributed submap strategy (DSS) is presented.
In its front-end, submap based scan matching is processed and loop closing detection is conducted. Moreover in
its back-end, pose graph is updated for global optimization and submap merging. From a series of experiments, it
is demonstrated that graph-based SLAM with DSS reduces 51.79% data overlap rate, decreases 39.70% runtime
and 24.60% memory usage. The advantages over other low overlap rate method is also proved in runtime, memory
usage, accuracy and robustness performance.

Key words： graph-based SLAM; distributed submap strategy; data overlap rate

Cite this article

XIANG Jiawei, ZHANG Jinyi, WANG Bin, MA Yongbin . Low Data Overlap Rate Graph-Based SLAM with Distributed Submap Strategy[J]. Journal of Shanghai Jiaotong University(Science), 2020 , 25(5) : 650 -658 . DOI: 10.1007/s12204-020-2201-4

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