ROBUST SENSOR BASED NAVIGATION FOR AUTONOMOUS MOBILE ROBOT

Immanuel Ashokaraj, Antonios Tsourdos, Peter Silson, Brian White

Abstract

This paper describes a new approach for mobile robot navigation using an interval analysis based adaptive mechanism for an Unscented Kalman filter. The robot is equipped with inertial sensors, encoders and ultrasonic sensors. The map used for this study is two-dimensional and it is assumed to be known a-priori. Multiple sensor fusion for robot localisation and navigation has attracted a lot of interest in recent years. An Unscented Kalman Filter (UKF) is used here to estimate the robots position using the inertial sensors and encoders. Since the UKF estimates are affected by bias, drift etc, we propose an adaptive mechanism using interval analysis with ultrasonic sensors to correct these defects in estimates. Interval analysis has been already successfully used in the past for robot localisation using time of flight sensors. But this IA algorithm has been extended to incorporate the sensor range limitation as in many real world sensors such as ultrasonic sensors. One of the problems of the use of interval analysis sensor based navigation and localisation is that it can be applicable only in the presence of land marks. This problem is overcome here using additional sensors such as encoders and inertial sensors, which gives an estimate of the robot position using an Unscented Kalman filter in the absence of land marks. In the presence of land marks the complementary robot position information from the Interval analysis algorithm using ultrasonic sensors is used to estimate and bound the errors in the UKF robot position estimate.

References

  1. Alessandri, A., Bartolini, G., Pavanati, P., Punta, E., and Vinci, A. (1997). An application of the ekf for integrated navigation in mobile robotics. American Control Conference.
  2. Castellanos, J. and Tardos, J. (1999). Mobile Robot Localisation and Map Building: A Multisensor Fusion Approach. Kluwer Ac. Pub., Boston.
  3. Clark, S., Dissanayake, G., Newman, P., and DurrantWhyte, H. (2001). A solution to slam problem. IEEE Journal of Robotics and Automation, 17(3).
  4. Jaulin, L., Kieffer, M., Didrit, O., and Walter, E. (2001). Applied Interval Analysis with examples in parameter and state estimation robust control and robotics. Springer-Verlag, London.
  5. Jaulin, L. and Walter, E. (1993). Set inversion via interval analysis for nonlinear bounded-error estimation. Automatica, 29(4):1053 to 1064.
  6. Jetto, L., Longhi, S., and Venturini, G. (1999). Development and experimental validation of an adaptive ekf for the localization of mobile robot. IEEE Transactions on Robotics and Automation, 15(2).
  7. Julier, S. and Uhlmann, J. (1997). A new extension of the kalman lter to nonlinear systems. In Proc. of Aerosense: The 11thInt. Symp. on Aerospace/Sensing, Simulation and Controls.
  8. Kieffer, M., Jaulin, L., Didrit, O., and Walter, E. (2000). Robust autonomous robot localization using interval analysis. Reliable Computing, 6(3):337 to 362.
  9. Kieffer, M., Jaulin, L., and Walter, E. (1998). Guaranteed recursive nonlinear state estimation using interval analysis. Internal Report, Laboratoire des Signaux et Systemes.
  10. Kieffer, M., Jaulin, L., Walter, E., and Meizel, D. (1999). Guaranteed mobile robot tracking using interval analysis. Proceedings of the MISC'99 Workshop on Applications of Interval Analysis to Systems and Control, page 347 to 359.
  11. Sorenson, H. (1990). Kalman ltering theory and application. IEEE press.
  12. Wan, E. and der Merwe, R. V. (2001). Kalman Filtering and Neural Networks, Chapter 7: The Unscented Kalman Filter. Wiley Publishing.
Download


Paper Citation


in Harvard Style

Ashokaraj I., Tsourdos A., Silson P. and White B. (2004). ROBUST SENSOR BASED NAVIGATION FOR AUTONOMOUS MOBILE ROBOT . In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 972-8865-12-0, pages 64-70. DOI: 10.5220/0001140500640070


in Bibtex Style

@conference{icinco04,
author={Immanuel Ashokaraj and Antonios Tsourdos and Peter Silson and Brian White},
title={ROBUST SENSOR BASED NAVIGATION FOR AUTONOMOUS MOBILE ROBOT},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2004},
pages={64-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001140500640070},
isbn={972-8865-12-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - ROBUST SENSOR BASED NAVIGATION FOR AUTONOMOUS MOBILE ROBOT
SN - 972-8865-12-0
AU - Ashokaraj I.
AU - Tsourdos A.
AU - Silson P.
AU - White B.
PY - 2004
SP - 64
EP - 70
DO - 10.5220/0001140500640070