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Precise Location Estimation Method Using a Localization Sensor for Goal Point Tracking of an Indoor Mobile Robot

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Information Technology Convergence

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 253))

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Abstract

Simultaneous localization is the most important research topic in mobile robotics. In this study, we propose a precise location estimation algorithm for a mobile robot based on a localization sensor and artificial landmarks in the ceiling in order to achieve point tracking. The proposed technique estimates the location of landmarks in the ceiling, generates the global ceiling and the global ceiling map for landmarks, and estimates the location of a mobile robot based on the ceiling map. The localization algorithm effectively removes incorrectly recognized landmarks using a histogram. In addition, the algorithm removes the measurement noise based on a Kalman filter. In order to evaluate the performance of the proposed precise localization technique, we performed several experiments using a mobile robot. The experimental results demonstrated the feasibility of the proposed localization algorithm.

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References

  1. Karlsson N, Bernardo ED, Ostrowski J, Goncalves L, Pirjanian P, Munich ME (2005) The vSLAM algorithm for robust localization and mapping. In: Proceedings of the IEEE Interference Conference on Robotics and Automation, pp 24–29

    Google Scholar 

  2. Montemerlo M (2003) Fast SLAM: A factored solution to the simultaneous localization and mapping problem with unknown data association. PhD thesis, Robotics Institute, Carnegie Mellon University

    Google Scholar 

  3. Dissanayake M, Newman P, Clark S, Durrant-Whyte H, Csorba M (2001) A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans Robotics Autom 17(3):229–241

    Google Scholar 

  4. Thrun S, Burgard W, Fox D (2005) Probabilistic robotics. MIT Press, Cambridge

    Google Scholar 

  5. Borenstein J, Feng L (1996) Measurement and correction of systematic odometry errors in mobile robots. IEEE Trans Robotics Autom 12(6):869–880

    Google Scholar 

  6. Pahlavan K, Li X, Makela J (2002) Indoor geolocation science and technology. IEEE Commun Mag 40(2):112–118

    Google Scholar 

  7. Liu J, Po Y (2007) A localization algorithm for mobile robots in RFID system. In: WiCon 2007 international conference on wireless communications, networking and mobile computing, pp 2109–2112

    Google Scholar 

  8. Lee S, Song J-B (2007) Mobile robot localization using infrared light-reflecting landmark. In: ICCAS ‘07 international conference on control, automation and system, pp 674–677

    Google Scholar 

  9. Wang H, Yu H, Kong L (2007) Ceiling light landmarks based localization and motion control for a mobile robot. IEEE International Conference on Networking, Sensing and Control, MonA01, pp 285–290

    Google Scholar 

  10. Welch G, Bishop G (2006) An introduction to the Kalman filter, UNC-Chapel Hill, TR 95-041

    Google Scholar 

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Correspondence to Tae-Kyu Yang .

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Park, SJ., Yang, TK. (2013). Precise Location Estimation Method Using a Localization Sensor for Goal Point Tracking of an Indoor Mobile Robot. In: Park, J., Barolli, L., Xhafa, F., Jeong, HY. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_95

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  • DOI: https://doi.org/10.1007/978-94-007-6996-0_95

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6995-3

  • Online ISBN: 978-94-007-6996-0

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