A Visual SLAM Algorithm based on Fuzzy Clustering for Removing Dynamic Features

IF 0.8 4区工程技术 Q4 ENGINEERING, MECHANICAL

Transactions of The Canadian Society for Mechanical Engineering Pub Date : 2023-03-24 DOI:10.1139/tcsme-2022-0090

Qinghui Zhou, Chenlong Zhang, Yuping He, Jie Huang

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引用次数: 0

Abstract

Most visual simultaneous localization and mapping (SLAM) algorithms assume that no or only few moving objects occur in application environments. This assumption makes the algorithms vulnerable to the interference of moving objects in dynamic environments. To address the problem, a new visual SLAM method, which could eliminate dynamic features without any prior information, was proposed. By measuring the position of each feature point and its motion vector difference between image sequences, a two-stage clustering was performed on the feature points in the field of view. This method removed the features detected on moving objects, and used a static initialization technique to eliminate the dependence of SLAM on prior information. The proposed method intended to improve OV2SLAM (A Fully Online and Versatile Visual SLAM for Real-Time Applications) algorithm, and the experimental verification was carried out. Our results show that while maintaining the real-time performance of the original OV2SLAM algorithm, the positioning accuracy and robustness of the proposed method is improved in a dynamic environment.

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基于模糊聚类的视觉SLAM动态特征去除算法

大多数视觉同时定位和映射（SLAM）算法都假设在应用程序环境中没有或只有很少的移动对象。这种假设使得算法容易受到动态环境中移动对象的干扰。为了解决这个问题，提出了一种新的视觉SLAM方法，该方法可以在没有任何先验信息的情况下消除动态特征。通过测量每个特征点的位置及其在图像序列之间的运动矢量差，对视场中的特征点进行两阶段聚类。该方法去除了在运动物体上检测到的特征，并使用静态初始化技术来消除SLAM对先验信息的依赖性。该方法旨在改进OV2SLAM（一种用于实时应用的全在线通用视觉SLAM）算法，并进行了实验验证。我们的结果表明，在保持原始OV2SLAM算法的实时性能的同时，该方法在动态环境中的定位精度和鲁棒性得到了提高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Transactions of The Canadian Society for Mechanical Engineering 工程技术-工程：机械

CiteScore

2.30

自引率

0.00%

发文量

审稿时长

5 months

期刊介绍： Published since 1972, Transactions of the Canadian Society for Mechanical Engineering is a quarterly journal that publishes comprehensive research articles and notes in the broad field of mechanical engineering. New advances in energy systems, biomechanics, engineering analysis and design, environmental engineering, materials technology, advanced manufacturing, mechatronics, MEMS, nanotechnology, thermo-fluids engineering, and transportation systems are featured.