Advertisement

Journal of Intelligent & Robotic Systems

, Volume 82, Issue 2, pp 325–337 | Cite as

Collaboration in Multi-Robot Exploration: To Meet or not to Meet?

  • Torsten Andre
  • Christian Bettstetter
Open Access
Article

Abstract

Work on coordinated multi-robot exploration often assumes that all areas to be explored are freely accessible. This common assumption does not always hold, especially not in search and rescue missions after a disaster. Doors may be closed or paths blocked detaining robots from continuing their exploration beyond these points and possibly requiring multiple robots to clear them. This paper addresses the issue how to coordinate a multi-robot system to clear blocked paths. We define local collaborations that require robots to collaboratively perform a physical action at a common position. A collaborating robot needs to interrupt its current exploration and move to a different location to collaboratively clear a blocked path. We raise the question when to collaborate and whom to collaborate with. We propose four strategies as to when to collaborate. Two obvious strategies are to collaborate immediately or to postpone any collaborations until only blocked paths are left. The other two strategies make use of heuristics based on building patterns. While no single strategy behaves optimal in all scenarios, we show that the heuristics decrease the time required to explore unknown environments considering blocked paths.

Keywords

Collaboration Robot exploration Mobile robot teams Indoor exploration Multi-robot systems Autonomous systems 

References

  1. 1.
    Alexander, C., Ishikawa, S., Silverstein, M.: A Pattern Language. Oxford University Press (1977)Google Scholar
  2. 2.
    Andre, T., Bettstetter, C.: Assessing the value of coordination in mobile robot exploration using a discrete-time Markov process. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2013)Google Scholar
  3. 3.
    Andre, T., Brandner, G., Marchenko, N., Bettstetter, C.: Measurement-based analysis of cooperative relaying in an industrial wireless sensor network. In: Proceedings of IEEE GLOBECOM (2012)Google Scholar
  4. 4.
    Andre, T., Neuhold, D., Bettstetter, C.: Coordinated multi-robot exploration: Out of the box packages for ROS. In: Proceedings of IEEE GLOBECOM WiUAV Workshop (2014)Google Scholar
  5. 5.
    Awerbuch, B., Betke, M., Rivest, R.L., Singh, M.: Piecemeal graph exploration by a mobile robot. Inf. Comput. 152(2), 155–172 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Burgard, W., Moors, M., Schneider, F.: Collaborative exploration of unknown environments with teams of mobile robots. In: Beetz, M., Hertzberg, J., Ghallab, M., Pollack, M. (eds.) Advances in Plan-Based Control of Robotic Agents, Lecture Notes in Computer Science, vol. 2466, pp. 52–70. Springer, Berlin (2002)Google Scholar
  7. 7.
    Burgard, W., Moors, M., Stachniss, C., Schneider, F.E.: Coordinated multi-robot exploration. IEEE Trans. Robot. 21, 376–386 (2005)Google Scholar
  8. 8.
    Bürger, G.: Personal communication (2014)Google Scholar
  9. 9.
    Dorigo, M., et al.: Swarmanoid: A novel concept for the study of heterogeneous robotic swarms. IEEE Robot. Autom. Mag. 20(4), 60–71 (2013)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Espinace, P., Kollar, T., Roy, N., Soto, A.: Indoor scene recognition by a mobile robot through adaptive object detection. Robot. Auton. Syst. 61(9), 932–947 (2013)Google Scholar
  11. 11.
    Espino, J.C., Steux, B., Hamzaoui, O.E.: Safe navigating system for indoor environments. In: Proceedings of 5th International Conference on Automation, Robotics and Applications (ICARA) (2011)Google Scholar
  12. 12.
    Farinelli, A., Iocchi, L., Nardi, D.: Multirobot systems: a classification focused on coordination. IEEE Trans. Syst., Man, Cybern. 34(5), 2015–2028 (2004)Google Scholar
  13. 13.
    Godsil, C., Royle, G.: Algebraic Graph Theory. Springer (2001)Google Scholar
  14. 14.
    González-Baños, H.H., Latombe, J.C.: Navigation strategies for exploring indoor environments. Int. J. Robot. Res. 21(10-11), 829–848 (2002)CrossRefGoogle Scholar
  15. 15.
    Hayes, A.: How many robots? Group size and efficiency in collective search tasks. In: Asama, H., Arai, T., Fukuda, T., Hasegawa, T. (eds.) Distributed Autonomous Robotic Systems 5, pp. 289–298. Springer, Japan (2002)Google Scholar
  16. 16.
    de Hoog, J., Cameron, S., Visser, A.: Selection of rendezvous points for multi-robot exploration in dynamic environments. In: Proceedings of International Conference on Auton. Agents and Multi-Agent Systems (AAMAS) (2010)Google Scholar
  17. 17.
    Juliá, M., Gil, A., Reinoso, O.: A comparison of path planning strategies for autonomous exploration and mapping of unknown environments. Auton. Robot. 33, 427–444 (2012)Google Scholar
  18. 18.
    Michael, N., Fink, J., Kumar, V.: Cooperative manipulation and transportation with aerial robots. Auton. Robot. 30, 73–86 (2011)CrossRefzbMATHGoogle Scholar
  19. 19.
    Mostofi, Y.: Communication-aware motion planning in fading environments. In: Proceedings of IEEE International Conference Robotics and Automation (ICRA) (2008)Google Scholar
  20. 20.
    Nevatia, Y., et al.: Augmented autonomy: Improving human-robot team performance in urban search and rescue. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2008)Google Scholar
  21. 21.
    Pei, Y., Mutka, M.W.: Joint bandwidth-aware relay placement and routing in heterogeneous wireless networks. In: Proceedings of IEEE International Conference on Parallel and Distributed Systems (ICPADS) (2011)Google Scholar
  22. 22.
    Singh, K., Fujimura, K.: Map making by cooperating mobile robots. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA) (1993)Google Scholar
  23. 23.
    Wurm, K.M., Dornhege, C., Eyerich, P., Stachniss, C., Nebel, B., Burgard, W.: Coordinated exploration with marsupial teams of robots using temporal symbolic planning. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2010)Google Scholar
  24. 24.
    Zlot, R.M., Stentz, A., Dias, M., Thayer, S.: Multi-robot exploration controlled by a market economy. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA) (2002)Google Scholar

Copyright information

© The Author(s) 2015

Authors and Affiliations

  1. 1.Networked and Embedded SystemsAlpen- Adria-Universität KlagenfurtKlagenfurtAustria
  2. 2.Lakeside Labs GmbHKlagenfurtAustria

Personalised recommendations