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

Guangbing Zhou (Shanghai University, Shanghai, China and South China Robotics Innovation Research Institute, Foshan, China)
Jing Luo (Wuhan University of Technology, Wuhan, China)
Shugong Xu (Shanghai University, Shanghai, China)
Shunqing Zhang (Shanghai University, Shanghai, China)
Shige Meng (South China Robotics Innovation Research Institute, Foshan, China)
Kui Xiang (Wuhan University of Technology, Wuhan, China)

Assembly Automation

ISSN: 0144-5154

Article publication date: 28 May 2021

Issue publication date: 22 July 2021




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.


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.


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.


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.



This article was funded by the Key-Area Research and Development Program of Guangdong Province (2020B0101130012) and Foshan Science and Technology Innovation Team Project (FS0AA-KJ919-4402-0060).


Zhou, G., Luo, J., Xu, S., Zhang, S., Meng, S. and Xiang, K. (2021), "An EKF-based multiple data fusion for mobile robot indoor localization", Assembly Automation, Vol. 41 No. 3, pp. 274-282.



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