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A Study on Localization of the Mobile Robot Using Inertial Sensors and Wheel Revolutions

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Book cover Intelligent Robotics and Applications (ICIRA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7101))

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Abstract

INS (Inertial Navigation System) is composed of inertial sensors such as accelerometers and gyroscopes and navigation computer. INS can estimate attitude and position by itself with no outside help and has acceptable stability in the short time, but poor stability in the long time. If a navigation system uses only INS, position and attitude errors are accumulated. The most basic and simple localization method is using encoders attached to robot’s wheels. However, measuring errors occur due to the slip between of wheel and ground. In this paper, we discuss about position estimation of the mobile robot in indoor environment. In order to achieve the optimal solution, the error model of encoder system and the Kalman filter will be designed. The system described in this paper shows better accurate position information.

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References

  1. Titterton, D.H., Weston, J.L.: Strapdown inertial navigation technology. The Institute of Electrical Engineers (2004)

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  2. Moon, W., Cho, B.S., Jang, J.W., Baek, K.R.: A Multi-Robot Positioning System using a Multi-Code Ultrasonic Sensor Network and a Kalman Filter. International Journal of Control, Automation and Systems 8(6), 1349–1355 (2010)

    Article  Google Scholar 

  3. Vaganay, J., Aldon, M.J., Fournier, A.: Mobile Robot Attitude Estimation by Fusion of Inertial Data. In: 1993 IEEE International Conference on Robotics and Automation, pp. 277–282 (1993)

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  4. Honghui, Q., Moore, J.: Direct Kalman Filtering Approach for GPS/INS Integration. IEEE Trans. on Aerospace and Electronic Systems 38(2), 687–693 (2002)

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  5. Welch, G., Bishop, G.: An Introduction to the Kalman Filter, July 24. UNC-Chapel Hill, TR 95-041 (2006)

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  6. Savage, P.G.: Strapdown Inertial Navigation Integration Algorithm Design Part 1: Attitude Algorithm. Journal of Guidance, Control, and Dynamics 21(1), 19–28 (1998)

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© 2011 Springer-Verlag Berlin Heidelberg

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Cho, BS., Moon, W., Seo, WJ., Baek, KR. (2011). A Study on Localization of the Mobile Robot Using Inertial Sensors and Wheel Revolutions. In: Jeschke, S., Liu, H., Schilberg, D. (eds) Intelligent Robotics and Applications. ICIRA 2011. Lecture Notes in Computer Science(), vol 7101. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25486-4_57

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  • DOI: https://doi.org/10.1007/978-3-642-25486-4_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25485-7

  • Online ISBN: 978-3-642-25486-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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