GraphTinker: Outlier Rejection and Inlier Injection for Pose Graph SLAM

Linhai Xie, Sen Wang, Andrew Markham, Niki Trigoni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)
95 Downloads (Pure)

Abstract

In pose graph Simultaneous Localization and Mapping (SLAM) systems, incorrect loop closures can seriously hinder optimizers from converging to correct solutions, significantly degrading both localization accuracy and map consistency. Therefore, it is crucial to enhance their robustness in the presence of numerous false-positive loop closures. Existing approaches tend to fail when working with very unreliable front-end systems, where the majority of inferred loop closures are incorrect. In this paper, we propose a novel middle layer, seamlessly embedded between front and back ends, to boost the robustness of the whole SLAM system. The main contributions of this paper are two-fold: 1) the proposed middle layer offers a new mechanism to reliably detect and remove false-positive loop closures, even if they form the overwhelming majority; 2) artificial loop closures are automatically reconstructed and injected into pose graphs in the framework of an Extended Rauch-Tung-Striebel smoother, reinforcing reliable loop closures. The proposed algorithm alters the graph generated by the front-end and can then be optimized by any back-end system. Extensive experiments are conducted to demonstrate significantly improved accuracy and robustness compared with state-of-the-art methods and various back-ends, verifying the effectiveness of the proposed algorithm.
Original languageEnglish
Title of host publication2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Pages6777-6784
Number of pages8
ISBN (Electronic)9781538626825
DOIs
Publication statusPublished - 14 Dec 2017
Event30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017 - Vancouver, Canada
Duration: 24 Sep 201728 Sep 2017

Publication series

NameIEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherIEEE
ISSN (Electronic)2153-0866

Conference

Conference30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017
Abbreviated titleIROS 2017
CountryCanada
CityVancouver
Period24/09/1728/09/17

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  • Cite this

    Xie, L., Wang, S., Markham, A., & Trigoni, N. (2017). GraphTinker: Outlier Rejection and Inlier Injection for Pose Graph SLAM. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6777-6784). (IEEE/RSJ International Conference on Intelligent Robots and Systems). IEEE. https://doi.org/10.1109/IROS.2017.8206596