Skip to main content
SpringerLink
Log in

Bearing-only Cooperative Localization

Simulation and Experimental Results

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

In cooperative localization a group of robots exchange relative position measurements from their exteroceptive sensors and their motion information from interoceptive sensors to collectively estimate their position and heading. For the localization errors to be bounded, it is required that the system be observable, independent of the estimation technique being used. In this paper, we develop a test-bed of three ground robots, which are equipped with wheel encoders and omnidirectional cameras, to implement the bearing-only cooperative localization. The simulation and experimental results validate the observability conditions, derived in Sharma et al. (IEEE Trans Robot 28:2, 2011), for the complete observability of the bearing-only cooperative localization problem.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Sharma, R., Beard, R.W., Taylor, C.N., Quebe, S.: Graph-based observability analysis of bearing-only cooperative localization. IEEE Trans. Robot. 28(2), 522–529 (2011)

    Article  Google Scholar 

  2. Kurazume, R., Hirose, S.: Study on cooperative positioning system: optimum moving strategies for CPS-III. In: Proc. IEEE International Conference on Robotics and Automation, vol. 4, 16–20, pp. 2896–2903 (1998)

  3. Sanderson, A.C.: A distributed algorithm for cooperative navigation among multiple mobile robots. Adv. Robot. 12, 335–349 (1998)

    Article  Google Scholar 

  4. Roumeliotis, S.I., Bekey, G.A.: Collective localization: a distributed kalman filter approach to localization of groups of mobile robots. In: Proc. IEEE International Conference on Robotics and Automation ICRA ’00, vol. 3, pp. 2958–2965 (2000)

  5. Spletzer, J., Das, A., Fierro, R., Taylor, C., Kumar, V., Ostrowski, J.: Cooperative localization and control for multi-robot manipulation. In: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 631–636 (2001)

  6. Rekleitis, I.M., Dudek, G., Milios, E.E.: Multi-robot cooperative localization: a study of trade-offs between efficiency and accuracy. In: Proc. IEEE/RSJ International Conference on Intelligent Robots and System, vol. 3, pp. 2690–2695 (2002)

  7. Nebot, P., Gomez, D., Cervera, E.: Agents for cooperative heterogeneous mobile robotics: a case study. In: Proc. IEEE International Conference on Systems, Man and Cybernetics, vol. 1, pp. 557–562 (2003)

  8. Bahr, A., Leonard, J.J., Fallon, M.F.: Cooperative localization for autonomous underwater vehicles. Int. J. Robot. Res. 28(6), 714–728 (2009)

    Article  Google Scholar 

  9. Mourikis, A., Roumeliotis, S.: Analysis of positioning uncertainty in reconfigurable networks of heterogeneous mobile robots. In: Proc. IEEE International Conference on Robotics and Automation ICRA ’04, vol. 1, pp. 572–579 (2004)

  10. Roumeliotis, S.I., Bekey, G.A.: Distributed multirobot localization. IEEE Trans. Robot. Auton. Syst. 18(5), 781–795 (2002)

    Article  Google Scholar 

  11. Howard, A., Matark, M.J., Sukhatme, G.S.: Localization for mobile robot teams using maximum likelihood estimation. In: Proc. IEEE/RSJ Int Intelligent Robots and Systems Conf, vol. 1, pp. 434–439 (2002)

  12. Fox, D., Burgard, W., Kruppa, H., Tharun, S.: A probabilistic approach to collaborative multi-robot localization. Auton. Robot. 8, 325–344 (2000)

    Article  Google Scholar 

  13. Nerurkar, E.D., Roumeliotis, S.I., Martinelli, A.: Distributed maximum a posteriori estimation for multi-robot cooperative localization. In: Proc. IEEE Int. Conf. Robotics and Automation ICRA ’09, pp. 1402–1409 (2009)

  14. Bicchi, A., Pratichizzo, D., Marigo, A., Balestrino, A.: On the observability of mobile vehicles localization. In: IEEE Mediterranean Conference on Control and Systems (1998)

  15. Huang, G., Mourikis, A., Roumeliotis, S.: Analysis and improvement of the consistency of extended kalman filter based SLAM. In: Proc. IEEE International Conference on Robotics and Automation ICRA 2008, pp. 473–479 (2008)

  16. Martinelli, A., Siegwart, R.: Observability analysis for mobile robot localization In: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005), pp. 1471–1476 (2005)

  17. Betke, M., Gurvits, L.: Mobile robot localization using landmarks. IEEE Trans. Robot. Auton. Syst. 13(2), 251–263 (1997)

    Article  Google Scholar 

  18. Perera, L.D.L., Melkumyan, A., Nettleton, E.: On the linear and nonlinear observability analysis of the SLAM problem. In: Proc. IEEE Int. Conf. Mechatronics ICM 2009, pp. 1–6 (2009)

  19. Lee, K.W., Wijesoma, W.S., Javier, I.G.: On the observability and observability analysis of SLAM. In: Proc. IEEE/RSJ Int Intelligent Robots and Systems Conf, pp. 3569–3574 (2006)

  20. Mourikis, A., Roumeliotis, S.: Performance analysis of multirobot cooperative localization. IEEE Trans. Robot. Auton. Syst. 22(4), 666–681 (2006)

    Article  Google Scholar 

  21. Song, Y., Grizzle, J.W.: The extended kalman filter as a local asymptotic observer for descrete -time nonlinear systems. J. Math. Syst. Estim. Contr. 5, 59–78 (1995)

    MathSciNet  MATH  Google Scholar 

  22. Hermann, R., Krener, A.: Nonlinear controllability and observability. IEEE Trans. Autom. Contr. 22(5), 728–740 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  23. Ethan Stump, V.K., Jadbabaie, A.: Connectivity management in mobile robot teams. In: IEEE International Conference on Robotics and Automation (2008)

  24. Sharma, R.: https://sites.google.com/site/rajnikantwiki/research/cooperative-localization (2011)

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, US Air Force Academy, Colorado Springs, CO, USA

    Rajnikant Sharma

  2. Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, USA

    Stephen Quebe & Randal W. Beard

  3. Air Force Research Lab, Wright Patterson Air Force Base, Dayton, OH, USA

    Clark N. Taylor

Authors
  1. Rajnikant Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stephen Quebe
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Randal W. Beard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Clark N. Taylor
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rajnikant Sharma.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sharma, R., Quebe, S., Beard, R.W. et al. Bearing-only Cooperative Localization. J Intell Robot Syst 72, 429–440 (2013). https://doi.org/10.1007/s10846-012-9809-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-012-9809-z

Keywords

Search

Navigation