Journal of Intelligent and Robotic Systems

, Volume 56, Issue 3, pp 259–276 | Cite as

Robust Robot Localization by Sensors with Different Degree of Accuracy

  • Gianluca Ippoliti
  • Alessia La Manna
  • Sauro Longhi


In this paper the robust robot localization problem with respect to uncertainties on environment features is formulated in a stochastic setting, and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, gyroscopic, and sonar measures. As gyroscopic readings are much more reliable than the other ones, the localization algorithm gives rise to a nearly singular EKF. This problem is dealt with by defining a reduced order nonsingular EKF. The robust solution has been implemented and tested on a powered wheelchair.


Mobile robot localization Kalman filtering Sensor fusion Autonomous systems Sensors Mechatronics 


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  1. 1.
    Gutmann, J.-S., Burgard, W., Fox, D., Konolige, K.: An experimental comparison of localization methods. In: Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, vol. 2, pp. 736–743. IEEE, Piscataway (1998)Google Scholar
  2. 2.
    Gutmann, J.-S., Fox, D.: An experimental comparison of localization methods continued. In: Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, vol. 1, pp. 454–459. IEEE, Piscataway (2002)CrossRefGoogle Scholar
  3. 3.
    Leonard, J.J., Durrant-Whyte, H.F.: Mobile robot localization by tracking geometric beacons. IEEE Trans. Robot. Autom. 7(3), 376–382 (1991, June)CrossRefGoogle Scholar
  4. 4.
    Arras, K.O., Castellanos, J.A., Schilt, M., Siegwart, R.: Feature-based multi-hypothesis localization and tracking using geometric constraints. Robot. Auton. Syst. 44(1), 41–53 (2003, July)CrossRefGoogle Scholar
  5. 5.
    Bonci, A., Ippoliti, G., Jetto, L., Leo, T., Longhi, S.: Methods and algorithms for sensor data fusion aimed at improving the autonomy of a mobile robot. In: Siciliano, B., De Luca, A., Melchiorri, C., Casalino, G. (eds.) Advances in Control of Articulated and Mobile Robots, Springer Tracts in Advanced Robotics, vol. 10, pp. 191–222. Springer, Berlin (2004)Google Scholar
  6. 6.
    Borenstein, J., Everett, H.R., Feng, L., Wehe, D.: Mobile robot positioning: sensors and techniques. J. Robot. Syst. 14(4), 231–249 (1997, Apr)CrossRefGoogle Scholar
  7. 7.
    Gu, J., Meng, M., Cook, A., Liu, P.X.: Sensor fusion in mobile robot: some perspectives. In: Proc. of the 4th World Congr. on Intelligent Control and Automation, vol. 2, pp. 1194–1199 (2002)Google Scholar
  8. 8.
    Bemporad, A., Di Marco, M., Tesi, A.: Sonar-based wall-following control of mobile robots. J. Dyn. Syst. Meas. Control 122(1), 226–229 (2000, Mar)CrossRefGoogle Scholar
  9. 9.
    Goel, P., Roumeliotis, S.I., Sukhatme, G.S.: Robust localization using relative and absolute position estimates. In: Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, vol. 2, pp. 1134–1140. IEEE, Piscataway (1999)Google Scholar
  10. 10.
    Lee, J., Yoshizawa, K., Hashimoto, H., Wada, M., Mori, S.: Advanced position estimation of mobile robots based on sensor fusion of rotary encoders and an optical fiber gyroscope. In: Proc. of the IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, pp. 109. IEEE, Piscataway (1997)CrossRefGoogle Scholar
  11. 11.
    Houshangi, N., Azizi, F.: Mobile robot position determination using data integration of odometry and gyroscope. In: Proc. of the World Automation Congr., pp. 1–8 (2006)Google Scholar
  12. 12.
    Miyake, N., Aono, T., Fujii, K., Matsuda, Y., Hatsumoto, S.: Position estimation and path control of an autonomous land vehicle. In: Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, vol. 2, pp. 690–696. IEEE, Piscataway (1997)Google Scholar
  13. 13.
    Tardós, J.D., Neira, J., Newman, P.M., Leonard, J.J.: Robust mapping and localization in indoor environments using sonar data. Int. J. Rob. Res. 21(4), 311–330 (2002, Apr)CrossRefGoogle Scholar
  14. 14.
    Borenstein, J., Koren, Y.: Histogramic in-motion mapping for mobile robot obstacle avoidance. IEEE Trans. Robot. Autom. 7(4), 535–539 (1991, Aug)CrossRefGoogle Scholar
  15. 15.
    Schroeter, C., Boehme, H.-J., Gross, H.-M.: Robust map building for an autonomous robot using low-cost sensors. In: Proc. of the IEEE Int. Conf. on Systems, Man and Cybernetics, vol. 6, pp. 5398–5403. IEEE, Piscataway (2004)Google Scholar
  16. 16.
    Thrun, S.: Robotic mapping: a survey. In: Lakemeyer, G., Nebel, B. (eds.) Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, San Francisco (2002)Google Scholar
  17. 17.
    Folkesson, J., Christensen, H.: Graphical SLAM—a self-correcting map. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, vol. 1, pp. 383–390. IEEE, Piscataway (2004)Google Scholar
  18. 18.
    Newman, P., Leonard, J., Tardós, J.D., Neira, J.: Explore and return: experimental validation of real-time concurrent mapping and localization. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, vol. 2, pp. 1802–1809. IEEE, Piscataway (2002)Google Scholar
  19. 19.
    Leonard, J.J., Feder, H.J.S.: Decoupled stochastic mapping. IEEE J. Oceanic Eng. 26(4), 561–571 (2001, Oct)CrossRefGoogle Scholar
  20. 20.
    Thrun, S., Fox, D., Burgard, W.: A probabilistic approach to concurrent mapping and localization for mobile robots. Mach. Learn. 31(1–3), 29–53 (1998) (Also appeared in Auton. Robots 5, 253–271 (joint issue))MATHCrossRefGoogle Scholar
  21. 21.
    Dellaert, F., Kaess, M.: Square root SAM: simultaneous localization and mapping via square root information smoothing. Int. J. Rob. Res. 25(12), 1181–1203 (2006, Dec)CrossRefGoogle Scholar
  22. 22.
    Eustice, R., Singh, H., Leonard, J., Walter, M., Ballard, R.: Visually navigating the RMS Titanic with SLAM information filters. In: Proc. of Robotics: Science and Systems, pp. 57–64 (2005)Google Scholar
  23. 23.
    Durrant-Whyte, H., Bailey, T.: Simultaneous localization and mapping: part I. IEEE Robot. Autom. Mag. 13(2), 99–110 (2006, June)CrossRefGoogle Scholar
  24. 24.
    Bailey, T., Durrant-Whyte, H.: Simultaneous localization and mapping (SLAM): part II. IEEE Robot. Autom. Mag. 13(3), 108–117 (2006, Sept)CrossRefGoogle Scholar
  25. 25.
    Dissanayake, M.W.M.G., Newman, P., Clark, S., Durrant-Whyte, H.F., Csorba, M.: A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans. Robot. Autom. 17(3), 229–241 (2001, June)CrossRefGoogle Scholar
  26. 26.
    Leonard, J.J., Durrant-Whyte, H.F.: Simultaneous map building and localization for an autonomous mobile robot. In: Proc. of the IEEE/RSJ Int. Workshop on Intelligent Robots and Systems, vol. 3, pp. 1442–1447. IEEE, Piscataway (1991)CrossRefGoogle Scholar
  27. 27.
    Anousaki, G.C., Kyriakopoulos, K.J.: Simultaneous localization and map building of skid-steered robots. IEEE Robot. Autom. Mag. 14(1), 79–89 (2007, Mar)CrossRefGoogle Scholar
  28. 28.
    Paz, L.M., Jensfelt, P., Tardós, J.D., Neira, J.: EKF SLAM updates in O(n) with Divide and Conquer SLAM. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 1657–1663. IEEE, Piscataway (2007)CrossRefGoogle Scholar
  29. 29.
    Guivant, J.E., Masson, F.R., Nebot, E.M.: Simultaneous localization and map building using natural features and absolute information. Robot. Auton. Syst. 40(2), 79–90 (2002, Aug)CrossRefGoogle Scholar
  30. 30.
    Armesto, L., Tornero, J.: SLAM based on Kalman filter for multi-rate fusion of laser and encoder measurements. In: Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, vol. 2, pp. 1860–1865. IEEE, Piscataway (2004)Google Scholar
  31. 31.
    Tomatis, N., Nourbakhsh, I., Siegwart, R.: Hybrid simultaneous localization and map building: a natural integration of topological and metric. Robot. Auton. Syst. 44(1), 3–14 (2003, July)CrossRefGoogle Scholar
  32. 32.
    Fioretti, S., Leo, T., Longhi, S.: A navigation system for increasing the autonomy and the security of powered wheelchairs. IEEE Trans. Rehabil. Eng. 8(4), 490–498 (2000, Dec)CrossRefGoogle Scholar
  33. 33.
    Bourhis, G., Horn, O., Habert, O., Pruski, A.: An autonomous vehicle for people with motor disabilities. IEEE Robot. Autom. Mag. 8(1), 20–28 (2001, Mar)CrossRefGoogle Scholar
  34. 34.
    Prassler, E., Scholz, J., Fiorini, P.: A robotic wheelchair for crowded public environments. IEEE Robot. Autom. Mag. 8(1), 38–45 (2001, Mar)CrossRefGoogle Scholar
  35. 35.
    Feil-Seifer, D., Matarić, M.J.: Defining socially assistive robotics. In: Proc. of the IEEE 9th Int. Conf. on Rehabilitation Robotics, pp. 465–468. IEEE, Piscataway (2005)Google Scholar
  36. 36.
    TGR-Bologna: TGR Explorer. Italy [Online]. (2007)
  37. 37.
    Wang, C.M.: Location estimation and uncertainty analysis for mobile robots. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 1230–1235. IEEE, Piscataway (1988)Google Scholar
  38. 38.
    Zhu, R., Zhang, Y., Bao, Q.: A novel intelligent strategy for improving measurement precision of FOG. IEEE Trans. Instrum. Meas. 49(6), 1183–1188 (2000, Dec)CrossRefGoogle Scholar
  39. 39.
    Chung, H., Ojeda, L., Borenstein, J.: Accurate mobile robot dead-reckoning with a precision-calibrated fiber-optic gyroscope. IEEE Trans. Robot. Autom. 17(1), 80–84 (2001, Feb)CrossRefGoogle Scholar
  40. 40.
    Blair, W.D., Bar-Shalom, Y.: Tracking maneuvering targets with multiple sensors: does more data always mean better estimates? IEEE Trans. Aerosp. Electron. Syst. 32(1), 450–456 (1996, Jan)CrossRefGoogle Scholar
  41. 41.
    Borenstein, J., Koren, Y.: Error eliminating rapid ultrasonic firing for mobile robot obstacle avoidance. IEEE Trans. Robot. Autom. 11(1), 132–138 (1995, Feb)CrossRefGoogle Scholar
  42. 42.
    Anderson, B.D.O., Moore, J.B.: Optimal Filtering. Dover, Mineola (2005)Google Scholar
  43. 43.
    Komoriya, K., Oyama, E.: Position estimation of a mobile robot using optical fiber gyroscope (OFG). In: Proc. of the Int. Conf. on Intelligent Robots and Systems, vol. 1, pp. 143–149 (1994)Google Scholar
  44. 44.
    Barshan, B., Durrant-Whyte, H.F.: Inertial navigation systems for mobile robots. IEEE Trans. Robot. Autom. 11(3), 328–342 (1995, June)CrossRefGoogle Scholar
  45. 45.
    Ojeda, L., Chung, H., Borenstein, J.: Precision-calibration of fiber-optics gyroscopes for mobile robot navigation. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, vol. 3, pp. 2064–2069 (2000)Google Scholar
  46. 46.
    Angeloni, A., Leo, T., Longhi, S., Zulli, R.: Real time collision avoidance for mobile robots. In: Proc. of the 6th Int. Symp. on Measurement and Control in Robotics, pp. 239–244 (1996)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Gianluca Ippoliti
    • 1
  • Alessia La Manna
    • 1
  • Sauro Longhi
    • 1
  1. 1.Dipartimento di Ingegneria Informatica, Gestionale e dell’AutomazioneUniversità Politecnica delle MarcheAnconaItaly

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