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A Method to Locate the Position of Mobile Robot Using Extended Kalman Filter

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

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Abstract

A method to estimate long distance navigation of a mobile robot is proposed. The method uses the dead reckoning,sonar and infrared sensors to detect the landmarks. A corridor environment with equal spaced convex edges is applied as the mobile robot’s moving space and the convex edges are used as landmarks for the robot mounted with the combined sensor system to estimate its position. The robot detects the convex edges using combined sensor system, and navigates in this corridor by using the information obtained from dead reckoning and combined sensor system based on the Extended Kalman. Experiment result show the effectiveness of the method.

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References

  1. Kidono, K., Miura, J., Shirai, Y.: Autonomous navigation of a mobile robot using a Human-Guided experience. In: Proc. Asian conf. on Computer Vision, pp. 449–454 (2000)

    Google Scholar 

  2. Moon, I., Miura, J., Shirai, Y.: Automatic extraction of visual landmarks for a mobile robot under uncertainty of vision and motion. In: Proc. 2001 IEEE Int. Conf. on Robotics and Automation, pp. 1188–1193 (2001)

    Google Scholar 

  3. Roumeliotis, S., Bekey, G.: Bayesian estimation and Kalman filtering: A unified framework for mobile robot localization. In: Proc. 2000 IEEE International Conference on Robotics and Automation, San Francisco, CA, April 22-28, pp. 2985–2992 (2000)

    Google Scholar 

  4. Goel, P., Dedeoglu, G., Roumeliotis, S.: Fault detection and identifcation in a mobile robot using multiple model estimation and neural network. In: Proc. 2000 IEEE International Conference on Robotics and Automation, San Francisco, CA, April 22-28, pp. 2302–2309 (2000)

    Google Scholar 

  5. Fengji, Z., Hai-jiao, G., Ken-Ichi, A.B.E.: Position location for a mobile robot using sonar sensors. In: IEEE International Conference on Intelligent Engineering Systems Vienna, Austria, pp. 130–135 (1998)

    Google Scholar 

  6. Beom, H., Cho, H.: Mobile robot localization using a single rotating sonar and two passive cylindrical beacons. Robotica 13, 243–252 (1995)

    Article  Google Scholar 

  7. Fengji, Z., Hai-jiao, G., Ken-Ichi, A.B.E.: Precise localization for a mobile robot with sonar and infrared sensors. In: IASTED International Conference Robotics and Manufacturing Banff, Canada, pp. 8–12 (1998)

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Wei, P., Xu, C., Zhao, F. (2005). A Method to Locate the Position of Mobile Robot Using Extended Kalman Filter. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_120

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  • DOI: https://doi.org/10.1007/11596448_120

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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