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A low-cost indoor positioning system based on data-driven modeling for robotics research and education

Published online by Cambridge University Press:  11 May 2023

Junlin Ou Open the ORCID record for Junlin Ou [Opens in a new window] ,
Seong Hyeon Hong ,
Tristan Kyzer ,
Haizhou Yang ,
Xianlian Zhou  and
Yi Wang
Junlin Ou
Affiliation:
Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA
Seong Hyeon Hong
Affiliation:
Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA
Tristan Kyzer
Affiliation:
Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA
Haizhou Yang
Affiliation:
Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Xianlian Zhou
Affiliation:
Department of Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
Yi Wang*
Affiliation:
Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA
*
Corresponding author: Yi Wang; Email: yiwang@cec.sc.edu
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Abstract

This paper presents a low-cost, accurate indoor positioning system that integrates image acquisition and processing and data-driven modeling algorithms for robotics research and education. Multiple overhead cameras are used to obtain normalized image coordinates of ArUco markers, and a new procedure is developed to convert them to the camera coordinate frame. Various data-driven models are proposed to establish a mapping relationship between the camera and the world coordinates. One hundred fifty data pairs in the camera and world coordinates are generated by measuring the ArUco marker at different locations and then used to train and test the data-driven models. With the model, the world coordinate values of the ArUco marker and its robot carrier can be determined in real time. Through comparison, it is found that a straightforward polynomial regression outperforms the other methods and achieves a positioning accuracy of about 1.5 cm. Experiments are also carried out to evaluate its feasibility for use in robot control. The developed system (both hardware and algorithms) is shared as an open source and is anticipated to contribute to robotic studies and education in resource-limited environments and underdeveloped regions.

Keywords

ArUco markerOpenCVindoor positioning systemimage processingdata-driven model
Type
Research Article
Information
Robotica , Volume 41 , Issue 9 , September 2023 , pp. 2648 - 2667
Copyright
© The Author(s), 2023. Published by Cambridge University Press

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