An EKF-based multiple data fusion for mobile robot indoor localization

IF 1.9 4区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Assembly Automation Pub Date : 2021-05-28 DOI:10.1108/AA-12-2020-0199
Guangbing Zhou, Jing Luo, Shugong Xu, Shunqing Zhang, Shige Meng, Kui Xiang
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引用次数: 7

Abstract

Purpose Indoor localization is a key tool for robot navigation in indoor environments. Traditionally, robot navigation depends on one sensor to perform autonomous localization. This paper aims to enhance the navigation performance of mobile robots, a multiple data fusion (MDF) method is proposed for indoor environments. Design/methodology/approach Here, multiple sensor data i.e. collected information of inertial measurement unit, odometer and laser radar, are used. Then, an extended Kalman filter (EKF) is used to incorporate these multiple data and the mobile robot can perform autonomous localization according to the proposed EKF-based MDF method in complex indoor environments. Findings The proposed method has experimentally been verified in the different indoor environments, i.e. office, passageway and exhibition hall. Experimental results show that the EKF-based MDF method can achieve the best localization performance and robustness in the process of navigation. Originality/value Indoor localization precision is mostly related to the collected data from multiple sensors. The proposed method can incorporate these collected data reasonably and can guide the mobile robot to perform autonomous navigation (AN) in indoor environments. Therefore, the output of this paper would be used for AN in complex and unknown indoor environments.
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基于EKF的移动机器人室内定位多数据融合
目的室内定位是机器人在室内环境中导航的关键工具。传统上,机器人导航依赖于一个传感器来执行自主定位。为了提高移动机器人的导航性能,提出了一种适用于室内环境的多数据融合方法。设计/方法/方法这里使用多个传感器数据,即惯性测量单元、里程表和激光雷达的收集信息。然后,使用扩展卡尔曼滤波器(EKF)来合并这些多个数据,移动机器人可以在复杂的室内环境中根据所提出的基于EKF的MDF方法进行自主定位。发现该方法已在不同的室内环境中进行了实验验证,如办公室、通道和展厅。实验结果表明,基于EKF的MDF方法在导航过程中可以获得最佳的定位性能和鲁棒性。原创性/价值室内定位精度主要与从多个传感器收集的数据有关。所提出的方法可以合理地结合这些收集的数据,并可以指导移动机器人在室内环境中进行自主导航。因此,本文的输出将用于复杂和未知的室内环境中的AN。
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来源期刊
Assembly Automation
Assembly Automation 工程技术-工程:制造
CiteScore
4.30
自引率
14.30%
发文量
51
审稿时长
3.3 months
期刊介绍: Assembly Automation publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of assembly technology and automation, and reflecting the most interesting and strategically important research and development activities from around the world. Because of this, readers can stay at the very forefront of industry developments. All research articles undergo rigorous double-blind peer review, and the journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations.
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