A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial Environment

In dynamic and complicated industrial environments, feature-based SLAM based on laser scanner is a popular choice to achieve localization of autonomous guided vehicles. However, there are many clutters and dynamic objects degrading SLAM performance. This paper proposes a clutter-resistant SLAM solut...

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Main Authors: Wei Wang, Yaohua Wu, Zhenyu Jiang, Jiahui Qi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9115027/
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author Wei Wang
Yaohua Wu
Zhenyu Jiang
Jiahui Qi
author_facet Wei Wang
Yaohua Wu
Zhenyu Jiang
Jiahui Qi
author_sort Wei Wang
collection DOAJ
description In dynamic and complicated industrial environments, feature-based SLAM based on laser scanner is a popular choice to achieve localization of autonomous guided vehicles. However, there are many clutters and dynamic objects degrading SLAM performance. This paper proposes a clutter-resistant SLAM solution where both point features generated from reflectors and line features are employed to improve SLAM robustness. First, a point feature recognition method based on geometrical characteristics of reflectors is developed to filter out clutters and identify true reflector landmarks; Then a dual-map based map management scheme is proposed for EKF-SLAM to further eliminate both types of fallacious landmarks and enhance its clutter resistance capability. The proposed methods eliminate adverse impact of clutters and thus improve SLAM performance in terms of accuracy, consistency and efficiency. The effectiveness of the proposed clutter-resistant SLAM solution is validated through real-time experiments. The absolute localization error is controlled within 19 mm and 31mm in X-axis and Y-axis respectively. The improved SLAM algorithm is proved to be accurate and efficient enough for practical application in dynamic and complicated industrial environments.
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spelling doaj-art-70ee7b1f48084a828f5508bfb0bee78c2025-08-20T03:22:00ZengIEEEIEEE Access2169-35362020-01-01810977010978210.1109/ACCESS.2020.30017569115027A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial EnvironmentWei Wang0https://orcid.org/0000-0002-2418-6490Yaohua Wu1https://orcid.org/0000-0002-5561-8049Zhenyu Jiang2https://orcid.org/0000-0002-5989-0584Jiahui Qi3https://orcid.org/0000-0002-0512-7911School of Control Science and Engineering, Shandong University, Ji’nan, ChinaSchool of Control Science and Engineering, Shandong University, Ji’nan, ChinaSchool of Control Science and Engineering, Shandong University, Ji’nan, ChinaSchool of Control Science and Engineering, Shandong University, Ji’nan, ChinaIn dynamic and complicated industrial environments, feature-based SLAM based on laser scanner is a popular choice to achieve localization of autonomous guided vehicles. However, there are many clutters and dynamic objects degrading SLAM performance. This paper proposes a clutter-resistant SLAM solution where both point features generated from reflectors and line features are employed to improve SLAM robustness. First, a point feature recognition method based on geometrical characteristics of reflectors is developed to filter out clutters and identify true reflector landmarks; Then a dual-map based map management scheme is proposed for EKF-SLAM to further eliminate both types of fallacious landmarks and enhance its clutter resistance capability. The proposed methods eliminate adverse impact of clutters and thus improve SLAM performance in terms of accuracy, consistency and efficiency. The effectiveness of the proposed clutter-resistant SLAM solution is validated through real-time experiments. The absolute localization error is controlled within 19 mm and 31mm in X-axis and Y-axis respectively. The improved SLAM algorithm is proved to be accurate and efficient enough for practical application in dynamic and complicated industrial environments.https://ieeexplore.ieee.org/document/9115027/EKFautonomous guided vehicleSLAMindustrial environment
spellingShingle Wei Wang
Yaohua Wu
Zhenyu Jiang
Jiahui Qi
A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial Environment
IEEE Access
EKF
autonomous guided vehicle
SLAM
industrial environment
title A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial Environment
title_full A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial Environment
title_fullStr A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial Environment
title_full_unstemmed A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial Environment
title_short A Clutter-Resistant SLAM Algorithm for Autonomous Guided Vehicles in Dynamic Industrial Environment
title_sort clutter resistant slam algorithm for autonomous guided vehicles in dynamic industrial environment
topic EKF
autonomous guided vehicle
SLAM
industrial environment
url https://ieeexplore.ieee.org/document/9115027/
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