Performance Analysis for Multi-robot Exploration Strategies

  • Sebastian Frank
  • Kim Listmann
  • Dominik Haumann
  • Volker Willert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6472)


In this note, we compare four different exploration strategies and analyze the performance in terms of exploration time and amount of exploration per time step. In order to provide a suitable reference for comparison, we derive an upper bound for the theoretically achievable increase of explored area per time step. The comparison itself is done using a comprehensive empirical evaluation resulting in statistically significant performance differences.


multi-robot exploration coordination distributed optimization 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Amigoni, F.: Experimental evaluation of some exploration strategies for mobile robots. In: Proc. 2008 IEEE Int. Conf. Rob. & Autom., pp. 2818–2823 (2008)Google Scholar
  2. 2.
    Aurenhammer, F.: Power diagrams: Properties, algorithms and applications. SIAM J. Comput. 16(1), 78–96 (1987)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Aurenhammer, F., Klein, R.: Vornoi diagrams. In: Handbook of Computational Geometry, ch. V, pp. 201–290. North-Holland, Amsterdam (2000)CrossRefGoogle Scholar
  4. 4.
    Calisi, D., Farinelli, A., Iocchi, L., Nardi, D.: Multi-objective exploration and search for autonomous rescue robots. J. Field Rob. 24(8-9), 763–777 (2007)CrossRefGoogle Scholar
  5. 5.
    Cortés, J., Martínez, S., Karatas, T., Bullo, F.: Coverage control for mobile sensing networks. IEEE Trans. Rob. Autom. 20(2), 243–255 (2004)CrossRefGoogle Scholar
  6. 6.
    Haumann, A.D., Listmann, K.D., Willert, V.: Discoverage: A new paradigm for multi-robot exploration. In: Proc. 2010 IEEE Int. Conf. Rob. & Autom., pp. 929–934 (2010)Google Scholar
  7. 7.
    Hussein, I., Stipanovic, D.: Effective coverage control for mobile sensor networks with guaranteed collision avoidance. IEEE Trans. Control Syst. Technol. 15(4), 642–657 (2007)CrossRefGoogle Scholar
  8. 8.
    Koren, Y., Borenstein, J.: Potential field methods and their inherent limitations for mobile robot navigation. In: Proc. 1991 IEEE Int. Conf. Rob. & Autom., pp. 1398–1404 (1991)Google Scholar
  9. 9.
    LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006)CrossRefzbMATHGoogle Scholar
  10. 10.
    Lee, D., Recce, M.: Quantitative evaluation of the exploration strategies of a mobile robot. Int. J. Rob. Res. 16(4), 413–447 (1997)CrossRefGoogle Scholar
  11. 11.
    Pavone, M., Arsie, A., Frazzoli, E., Bullo, F.: Equitable partitioning policies for robotic networks. In: Proc. 2009 IEEE Int. Conf. Rob. & Autom., pp. 2356–2361 (2009)Google Scholar
  12. 12.
    Simmons, R., Apfelbaum, D., Burgard, W., Fox, M., an Moors, D., Thrun, S., Younes, H.: Coordination for multi-robot exploration and mapping. In: Proc. AAAI Nat. Conf. Art. Intell. (2000)Google Scholar
  13. 13.
    Solanas, A., Garcia, M.A.: Coordinated multi-robot exploration through unsupervised clustering of unknown space. In: Proc. IEEE/RSJ Int. Conf. Intell. Rob. & Syst., pp. 852–858 (2004)Google Scholar
  14. 14.
    Tukey, J.W.: Exploratory Data Analysis. Addison-Wesley, Reading (1977)zbMATHGoogle Scholar
  15. 15.
    Yamauchi, B.: A frontier-based approach for autonomous exploration. In: Proc. IEEE Int. Symp. Comput. Intell., Rob. & Autom., pp. 146–151 (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Sebastian Frank
    • 1
  • Kim Listmann
    • 1
  • Dominik Haumann
    • 1
  • Volker Willert
    • 1
  1. 1.Control Theory & Robotics LabTU DarmstadtDarmstadtGermany

Personalised recommendations