Beacon Scheduling Algorithm for Localization of a Mobile Robot

  • Jaehyun Park
  • Sunghee Choi
  • Jangmyung Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7101)


This paper proposes the localization scheme using ultrasonic beacons in a multi-block workspace. Indoor localization schemes using ultrasonic sensors have been widely studied due to their cheap price and high accuracy. However, ultrasonic sensors are susceptible to environmental noises from their propagation characteristics. On account of their decay phenomena when they are transmitted over a long distance, ultrasonic sensors are not suitable for application in large indoor environments. To overcome these shortages of ultrasonic sensors while emphasizing their advantages, a multi-block approach has been proposed by dividing the indoor space into several blocks with multiple beacons in each block. This approach, however, is hard to divide into several blocks when beacons are not installed in a certain pattern, and in case of having newly installed beacons, all blocks placement is reconstructed. Therefore, this paper proposes a real time localization scheme to estimate the position of mobile robot without effecting beacons placement. Beacon scheduling algorithm has been developed to select the optimal beacons according to robot position and beacon arrangement for the mobile robot navigation. The performance of the proposed localization system is verified through simulations and real experiments.


Mobile robot Localization Ultrasonic Beacon Beacon Scheduling 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Myung, H., et al.: Mobile robot localization with gyroscope and constrained Kalman filter. International Journal of Control, Automation, and Systems 8(3), 667–676 (2010)CrossRefGoogle Scholar
  2. 2.
    Borenstein, J., Feng, L.: Measurement and correction of systematic odometry errors in mobile robots. IEEE Transactions on Robotics and Automation 12, 869–880 (1996)CrossRefGoogle Scholar
  3. 3.
    Tsai, C.C.: A Localization System of a Mobile Robot by Fusing Dead-reckoning and Ultrasonic Measurements. IEEE Transactions on Industrial Electronics 47(5), 1399–1404 (1998)MathSciNetGoogle Scholar
  4. 4.
    Abuhashim, T.S., Adbedl-Hagez, M.F., Al-Jarrah, M.A.: Building a Robust Integrity Monitoring Algorithm for a Low Cost GPS-aided-INS System. International Journal of Control, Automation, and Systems 8(5), 1108–1122 (2010)CrossRefGoogle Scholar
  5. 5.
    Sooyong, L., Song, J.-B.: Mobile Robot Localization using Range Sensors: Consecutive Scanning and Cooperative Scanning. International Journal of Control, Automation, and Systems 3(1), 1–14 (2005)Google Scholar
  6. 6.
    Ngai, M.K., Quang, P.H., Shoudong, H., Gamini, D., Gu, F.: Mobile Robot Localization and Mapping using a Gaussian Sum Filter. International Journal of Control, Automation, and Systems 5(3), 251–268 (2007)Google Scholar
  7. 7.
    Lee, Y.J., Yim, B.D., Song, J.B.: Mobile Robot Localization based on Effective Combination of Vision and Range Sensors. International Journal of Control, Automation, and Systems 7(1), 97–104 (2007)CrossRefGoogle Scholar
  8. 8.
    Han, S.S., Lim, H.S., Lee, J.M.: An Efficient Localization Scheme for a Differential-Driving Mobile Robot Based on RFID System. IEEE Trans. on Industrial Electronics 54(6), 1–8 (2007)CrossRefGoogle Scholar
  9. 9.
    Park, J.H., Choi, M.G., Lee, J.M.: Indoor Localization System in a Multi-block Workspace. Robotica 28, 397–403 (2010)CrossRefGoogle Scholar
  10. 10.
    Ching, C.T.: A Localization System of a Mobile Robot by Fusing Dead-reckoning and Ultrasonic. IEEE Trans. on Instrumentation and Measurement 47, 1399–1404 (1998)CrossRefGoogle Scholar
  11. 11.
    Qinhe, W., Hashimoto, H.: Fast Localization of Multi-targets in the Intelligent Space. In: Annual Conf. SICE 2007, pp. 264–269 (2007)Google Scholar
  12. 12.
    Seo, D.G., Lee, J.M.: Localization Algorithm for a Mobile Robot Using iGS. In: The 17th International Federation of Automatic Control World Congress, pp. 742–747 (2008)Google Scholar
  13. 13.
    Manolakis, D.E.: Efficient Solution and Performance Analysis of 3D Position Estimation by Trilateration. IEEE Trans. on Aerospace and Electronic Systems 32, 1239–1248 (1996)CrossRefGoogle Scholar
  14. 14.
    Thomas, F., Ros, L.: Revisiting Trilateration for Robot Localization. IEEE Trans. on Robotics 21, 93–101 (2005)CrossRefGoogle Scholar
  15. 15.
    Barshan, B.: Fast Processing Techniques for Accurate Ultrasonic Range Measurements. IOP J. Meas. Sci. Technology 11, 45–50 (2000)CrossRefGoogle Scholar
  16. 16.
    Eom, W.S., Lee, J.M.: Ubiquitous Positioning Network of a Mobile Robot with Active Beacon Sensors. In: Int. Conf. on Circuits/System, Computers and Communications, pp. 255–256 (2007)Google Scholar
  17. 17.
    Yi, S.Y., Choi, B.W.: Autonomous Navigation of Indoor Mobile Robots Using a Global Ultrasonic System. Robotica 22, 369–374 (2004)CrossRefGoogle Scholar
  18. 18.
    Kim, S.B., Lee, J.M., Lee, I.O.: Precise Indoor Localization System For a Mobile Robot Using Auto Calibration Algorithm. In: The 13th International Conference on Advanced Robotics, pp. 635–640 (2007)Google Scholar
  19. 19.
    Eom, W.S., Park, J.H., Lee, J.M.: Hazardous Area Navigation with Temporary Beacons. International Journal of Control, Automation, and Systems 8(5), 1082–1090 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jaehyun Park
    • 1
  • Sunghee Choi
    • 1
  • Jangmyung Lee
    • 1
  1. 1.Dept. of Electrical EngineeringPusan National UniversitySouth Korea

Personalised recommendations