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Effects of Augmented Reality Markers for Networked Robot Navigation

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Advances in Intelligent Networking and Collaborative Systems (INCoS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 312))

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Abstract

The authors have studied augmented reality techniques applied to a support robot navigation system. It helps care recipients to remotely control robots for themselves with simple commands through a communication network. This paper focuses on the identification and geometrical measurement of planar markers with mosaic patterns. Experiments reveal that the identification rate as well as measurement accuracy is related to feature points of the pattern. They also clarify that there is a positive correlation between the number of feature points and the accuracy of marker recognition. This research project also proposes the optimum AR markers for networked welfare robot navigation.

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Acknowledgments

This works was supported by JKA and its promotion funds from KEIRIN RACE.

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Authors and Affiliations

  1. Graduate School of Science and Engineering, Saga University, Saga, Japan

    Masato Ogata & Masato Inoue

  2. Department of Mechanical Systems Engineering, Saga University, Saga, Japan

    Kiyotaka Izumi & Takeshi Tsujimura

Authors
  1. Masato Ogata
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  2. Masato Inoue
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  3. Kiyotaka Izumi
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  4. Takeshi Tsujimura
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Corresponding author

Correspondence to Masato Ogata .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan

    Hsing-Chung Chen

  3. School of Science and Technology, Kwansei Gakuin University, Sanda, Japan

    Hiroyoshi Miwa

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Ogata, M., Inoue, M., Izumi, K., Tsujimura, T. (2022). Effects of Augmented Reality Markers for Networked Robot Navigation. In: Barolli, L., Chen, HC., Miwa, H. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2021. Lecture Notes in Networks and Systems, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-84910-8_2

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