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Improvement of Dust Detection System Using Infra-red Sensors

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Robot Intelligence Technology and Applications 3

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 345))

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Abstract

This paper proposes a sensor, which is capable of determining the type of dust through the dust detection sensor system that uses infrared sensor. Recently, cleaning robot is highly favored in the service robot market, which has been lead to development in various fields. Researches including navigation, localization, and developing the key components are underway to improve the performance, where the researches related to sensor are actively progressed accordingly. The dust detection device is developed to improve the performance of cleaning robot by determining the type of dust. The developed dust detection device is consists up of 1 transmitter and 24 receivers. The amount of transmitted and reflected light emanated from light sensor varies according to the characteristics of various types of dust, which passes through the middle of the dust detection device. The changes in the amount of light from 24 receivers are collected as the experiment data using the test bed of proposed dust detection device. Lastly, this paper confirms determining the type of dust by analyzing the pattern using the pixel-based dust similarity method.

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References

  1. Fink, J., et al.: Living with a Vacuum Cleaning Robot. International Journal of Social Robotics 2, 1–20 (2013); Bruce, K.B., Cardelli, L., Pierce, B.C.: Comparing Object Encodings. In: Abadi, M., Ito, T. (eds.) TACS 1997. LNCS, vol. 1281, pp. 415–438. Springer, Heidelberg (1997)

    Google Scholar 

  2. Jodi, F., DiSalvo, C.: Service Robots in the Domestic Environment: A Study of the Roomba Vacuum in the Home. In: Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction, pp. 258–265. ACM (2006)

    Google Scholar 

  3. Nam, M.-K.: A Study on present Condition of Development and Market of Artificial Intelligence Robot In and Out of Country. Journal of the Korean Society of Design Culture 16(2), 198–207 (2010)

    Google Scholar 

  4. Batalin, M.A., Sukhatme, G.S., Hattig, M.: Mobile Robot Navigation Using a Sensor Network. In: Proceedings of the 2004 IEEE International Conference on Robotics and Automation, ICRA 2004, vol. 1. IEEE (2004)

    Google Scholar 

  5. Doh, N.L., Kim, C., Chung, W.K.: A practical path planner for the robotic vacuum cleaner in rectilinear environments. IEEE Transactions on Consumer Electronics 53(2), 519–527 (2007)

    Article  Google Scholar 

  6. Kim, H., et al.: User-Centered Approach to Path Planning of Cleaning Robots: Analyzing User’s Cleaning Behavior. In: Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, pp. 273–380. ACM (2007)

    Google Scholar 

  7. Chen, Z., Birchfield, S.T.: Qualitative Vision-based Mobile Robot Navigation. In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation, ICRA 2006, pp. 2686–2692. IEEE (2006)

    Google Scholar 

  8. Freire, E., et al.: A New Mobile Robot Control Approach via Fusion of Control Signals. IEEE Transaction on Systems, Man, and Cybernetics, Part B: Cybernetics 34(1), 419–429 (2004)

    Article  Google Scholar 

  9. Kawakami, H., et al.: Dust detector for vacuum cleaner. U.S. Patent No. 5,163,202 (November 17, 1992)

    Google Scholar 

  10. Kim, D.-H., Min, B.-C., Kim, D.-H.: A Dust Detection Sensor System for Improvement of a Robot Vacuum Cleaner. Journal of Institute of Control, Robotics and Systems 10, 896-500(5 pages) (2013)

    Google Scholar 

  11. Ascenso, J., Brites, C., Pereira, F.: Motion compensated refinement for low complexity pixel based distributed video coding. In: IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2005. IEEE (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics and Radio Engineering, Kyung Hee University, Yongin, 446-701, Republic of Korea

    Donghoe Kim, Wonse Jo & Donghan Kim

  2. Department of Electrical Engineering, Myongji University, Yongin, Korea

    Bumjoo Lee

  3. DGIST, Pragmatic Applied Robot Institute, Daegu, 771-873, Republic of Korea

    Jinung An

Authors
  1. Donghoe Kim
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  2. Wonse Jo
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  3. Bumjoo Lee
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  4. Jinung An
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  5. Donghan Kim
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Corresponding author

Correspondence to Donghoe Kim .

Editor information

Editors and Affiliations

  1. Div. Electrical Engineering, Korea Advanced Institute of Science & Technology (KAIST), Daejeon, Korea, Republic of (South Korea)

    Jong-Hwan Kim

  2. College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China

    Weimin Yang

  3. School of Information and Communication Technology, Griffith University, Gold Coast, Australia

    Jun Jo

  4. Center for Intelligent Technologies, Technical University of Kosice, Kosice, Slovakia

    Peter Sincak

  5. Civil and Environmental Engg., KAIST, Daejeon, Korea, Republic of (South Korea)

    Hyun Myung

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© 2015 Springer International Publishing Switzerland

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Kim, D., Jo, W., Lee, B., An, J., Kim, D. (2015). Improvement of Dust Detection System Using Infra-red Sensors. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_63

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  • DOI: https://doi.org/10.1007/978-3-319-16841-8_63

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16840-1

  • Online ISBN: 978-3-319-16841-8

  • eBook Packages: EngineeringEngineering (R0)

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