Toward the Concept of Robot Society: A Multi-Robot SLAM Case Study

  • Micael S. Couceiro
  • Andria R. Lopes
  • N. M. Fonseca Ferreira
  • Anabela G. Ferreira
  • Rui Rocha
Conference paper


Over time, biological societies such as humans, ants or bees have shown us the advantages inherent to the collective work. It is based on such results that many researchers have been trying to successfully develop new approaches in Multi-Robot Systems. Nevertheless, several assumptions need to be assured for collective work to emerge. In this paper, it is presented the significance and the advantages of cooperation in the different societies bridging the gap to the concept of robot society. In order to compare the advantages of cooperative robots, it is considered essential the development of computational simulation based on the robotic cooperation in unstructured environments. Hence, a Multi-Robot Simultaneous Localization and Mapping (SLAM) using Rao-Blackwellized particle filter is implemented in a simulation environment developed in the Player/ Stage platform for robot and sensor applications.


Robot Society Cooperation Multi-robot slam 



This work was supported by a PhD scholarship (SFRH/BD/73382/2010) granted by the Portuguese Foundation for Science and Technology (FCT), the Institute of Systems and Robotics (ISR) and RoboCorp.


  1. 1.
    Halme A, Jakubik P, Schönberg T, Vainio M (1993) The concept of robot society and its utilization. In: Proceedings of IEEE international workshop on advanced robotics, Espoo, FinlandGoogle Scholar
  2. 2.
    Ferreira NMF (2006) Sistemas Dinâmicos e Controlo de Robôs Cooperantes. The Phd thesis (in 5 of September) University of Trás-os-Montes e Alto DouroGoogle Scholar
  3. 3.
    Fukuda T, Nakagawa S, Kawauchi Y, Buss M (1989) Structure decision method for self organizing robots based on cell structures—CEBOT. In: Proceedings of IEEE international conference on robotics and automation, pp 695–700, Scottsdale, AZGoogle Scholar
  4. 4.
    Rocha R (2006) Building volumetric maps with cooperative mobile robots and useful information sharing: a distributed control approach based on entropy. PhD thesis, Faculty of Engineering of University of Porto, Portugal, May 2006Google Scholar
  5. 5.
    Howard, A (2006) Multi-robot SL, mapping using particle filters. Int J Robot Res 25(12):1243–1256CrossRefGoogle Scholar
  6. 6.
    Darwin, C (1872) The origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. John Murray, LondonGoogle Scholar
  7. 7.
    Foster KR, Xavier JB (2007) Cooperation: bridging ecology and sociobiology. Curr Biol 17:R319–R321CrossRefGoogle Scholar
  8. 8.
    Dean, M (1913) Book of Proverbs. Catholic encyclopedia. Adapted from Holman Bible Handbook on ProverbsGoogle Scholar
  9. 9.
    Aras R, Dutech A, Charpillet F (2004) Stigmergy in multi agent reinforcement learning. Loria, Inst. Nat de Recherche en Inf et Autom, NancyGoogle Scholar
  10. 10.
    Dorigo, M, Stützle T (2004) Ant colony optimization. MIT Press, CambridgeCrossRefzbMATHGoogle Scholar
  11. 11.
    Wilson M, Melhuish C, Sendova-Franks A, Scholes S (2004) Algorithms for building annular structures with minimalist robots inspired by brood sorting in ant colonies. Auton Robot 17(2–3):115–136CrossRefGoogle Scholar
  12. 12.
    Kennedy J, Eberhart R (1995) A new optimizer using particle swarm theory. In: Proceedings of the IEEE sixth international symposium on micro machine and human science, pp 39–43, NagoyaGoogle Scholar
  13. 13.
    Tang J, Zhu J, Sun Z (2005) A novel path planning approach based on AppART and particle swarm optimization. Advances in Neural Networks–ISNN 2005. Springer Berlin Heidelberg, pp 253–258Google Scholar
  14. 14.
    Pires EJS, Oliveira PBM, Machado JAT, Cunha JB (2006) Particle swarm optimization versus genetic algorithm in manipulator trajectory planning. In: 7th Portuguese conference on automatic contol, Instituto Superior Técnico, Lisbon, Portugal, 11–13 Sept 2006Google Scholar
  15. 15.
    Couceiro MS, Mendes R, Ferreira NMF, Machado JAT (2009) Control optimization of a robotic bird. EWOMS ’09, Lisbon, Portugal, 4–6 June, 2009Google Scholar
  16. 16.
    Alrashidi MR, El-Hawary MEA (2006) Survey of particle swarm optimization applications in power system operations. Electric Power Compon Syst 34(12):1349–1357CrossRefGoogle Scholar
  17. 17.
    Martinez JR, Merino L, Caballero F, Ollero A, Viegas DX (2006) Experimental results of automatic fire detection and monitoring with UAVs. For Ecol Manage 234:232Google Scholar
  18. 18.
    Couceiro MS, Figueiredo CM, Ferreira NMF, Machado JAT (2009) Biological inspired flying robot. In: Proceedings of IDETC/CIE 2009 ASME 2009 international design engineering technical conferences & computers and information in engineering conference, San Diego, 30 Aug–2 Sept 2009Google Scholar
  19. 19.
    Borghoff UM, Schlighter JH (2000) Computer-supported cooperative work: introduction to distributed applications. Springer, USACrossRefGoogle Scholar
  20. 20.
    Fuks H, Raposo AB, Gerosa MA, Lucena CJPO (2003) Modelo de Colaboração 3C e a Engenharia de Groupware. Pontifícia Universidade Católica, Rio de Janeiro (PUC-Rio)Google Scholar
  21. 21.
    Cao Y, Fukunaga A, Kahng A (1997) Cooperative mobile robotics: antecedents and directions. Auton Robot 4:1–23CrossRefGoogle Scholar
  22. 22.
    Jung, D (1998) An architecture for cooperation among autonomous agents. PhD thesis, Department of Computer Science, University of Wollongong, AustraliaGoogle Scholar
  23. 23.
    Smith R, Self M, Cheeseman P (1990) Estimating uncertain spatial relationships in robotics. In: Ingemar JC, Gordon TW (eds) Autonomous robot vehicles. Springer, New York, pp 167–193Google Scholar
  24. 24.
    Dissanayake M, Newman P, Clark S, Durrant-Whyte H, Csorba M (2001) A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans Robot Autom, 17(3):229–241CrossRefGoogle Scholar
  25. 25.
    Thrun S, Dirk H, David F, Montemerlo D, Rudolph T, Wolfram B, Christopher B, Zachary O, Scott T, William W (2003) A system for volumetric robotic mapping of abandoned mines. Robotics and Automation, 2003. Proceedings. ICRA’03. IEEE International Conference on, vol. 3, pp. 4270–4275. IEEEGoogle Scholar
  26. 26.
    Thrun S, Dirk H, David F, Montemerlo D, Rudolph T, Wolfram B, Christopher B, Zachary O, Scott T,WilliamW (2003) A system for volumetric robotic mapping of abandoned mines. Robotics and Automation, 2003. Proceedings. ICRA’03. IEEE International Conference on ,vol. 3, pp. 4270–4275. IEEEGoogle Scholar
  27. 27.
    Stachniss C, Hahnel D, Burgard W (2004) Exploration with active loop-closing for FastSLAM. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems, Department of Computer Science, Freiburg University, GermanyGoogle Scholar
  28. 28.
    Stachniss C, Grisetti G, Burgard W (2005) Recovering particle diversity in a Rao-Blackwellized particle filter for SLAM after actively closing loops. In: Proceedings of IEEE international conference on robotics and automation, Freiburg, GermanyGoogle Scholar
  29. 29.
    Hahnel D, Burgard W, Fox D (2003) An efficient FastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements. In: IEEE/RSJ international conference on intelligent robots and systems, Las Vegas, Nevada, USA, Oct 2003Google Scholar
  30. 30.
    Thrun S, Fox D, Burgard W (2001) Robust Monte Carlo localization for mobile robots. Artif Intell J 128(1–2):99–141CrossRefzbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Micael S. Couceiro
    • 1
    • 2
  • Andria R. Lopes
    • 3
  • N. M. Fonseca Ferreira
    • 2
  • Anabela G. Ferreira
    • 4
  • Rui Rocha
    • 1
  1. 1.Institute of Systems and RoboticsUniversity of CoimbraCoimbraPortugal
  2. 2.RoboCorp, Department of Electrotechnics EngineeringEngineering Institute of CoimbraCoimbraPortugal
  3. 3.Faculty of Economics of CoimbraUniversity of CoimbraCoimbraPortugal
  4. 4.Coimbra School of EducationCoimbraPortugal

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