Advertisement

Sensor Fusion: An Application to Localization and Obstacle Avoidance in Robotics Using Multiple IR Sensors

  • Rahul Sharma
  • Honc Daniel
  • František Dušek
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 289)

Abstract

Sensor fusion brings the advantage of combining data from various sensors and there by generating a more accurate prediction or estimation of data. Over dependency of sensor and estimation from unreliable data are the most challenging tasks in mobile robotics. In this paper, a framework of sensor fusion technique is presented. The data from the multiple sensors are fused together and the parameters and crash time are estimated. The experiment results show that the sensor fusion technique provides solution to over dependency of sensor and problems with estimation of data from unreliable data. The technique finds application in obstacle avoidance and localization of mobile robots.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Elmenreich, W.: A review on system architectures for sensor fusion applications. In: Obermaisser, R., et al. (eds.) SEUS 2007. LNCS, vol. 4761, pp. 547–559. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Foxlin, E.: Inertial head-tracker sensor fusion by a complementary separate-bias Kalman filter. In: Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium, pp. 185–194. IEEE (March 1996)Google Scholar
  3. 3.
    Jetto, L., Longhi, S., Venturini, G.: Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots. IEEE Transactions on Robotics and Automation 15(2), 219–229 (1999)CrossRefGoogle Scholar
  4. 4.
    Kam, M., Zhu, X., Kalata, P.: Sensor fusion for mobile robot navigation. Proceedings of the IEEE 85(1), 108–119 (1997)CrossRefGoogle Scholar
  5. 5.
    Naji, H.R., Weir, J., Wells, B.E.: Applying the multi-agent paradigm to reconfigurable hardware: a sensor fusion example. In: Second International Workshop on Intelligent Systems Design and Application, pp. 207–212. Dynamic Publishers, Inc. (January 2002)Google Scholar
  6. 6.
    Nicosevici, T., Garcia, R., Carreras, M., Villanueva, M.: A review of sensor fusion techniques for underwater vehicle navigation. In: OCEANS 2004, MTTS/IEEE TECHNO-OCEAN 2004, vol. 3, pp. 1600–1605. IEEE (2004)Google Scholar
  7. 7.
    Panich, S., Afzulpurkar, N.: Sensor Fusion Techniques in Navigation Application for Mobile Robot. In: Sensor Fusion-Foundation and Applications, pp. 101–120 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Process control, Faculty of Electrical Engineering and InformaticsUniversity of PardubicePardubiceCzech Republic

Personalised recommendations