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Towards a Further Understanding of the Robotic Darwinian PSO

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Computational Intelligence and Decision Making

Part of the book series: Intelligent Systems, Control and Automation: Science and Engineering ((ISCA,volume 61))

Abstract

This paper presents a statistical significance analysis of a modified version of the Particle Swarm Optimization (PSO) on groups of simulated robots performing a distributed exploration task, denoted as RDPSO (Robotic DPSO). This work aims to evaluate this novel exploration strategy studying the performance of the algorithm under communication constraints while increasing the population of robots. Experimental results show that there is no linear relationship between the number of robots and the maximum communication range. In general, the decreased performance by the developed algorithm under communication constraints can be overcome by slightly increasing the number of robots as the maximum communication range is decreased.

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References

  1. Floreano D, Mattiussi C (2008) Bio-inspired artificial intelligence: theories, methods, and technologies. MIT Press, Cambridge

    Google Scholar 

  2. Marques L, de Almeida AT (2004) Finding odours across large search spaces: a particle swarm-based approach. In: Proceedings of the 6th international conference on Climbing & Walking Robots (CLAWAR), Madrid, Spain

    Google Scholar 

  3. Marjovi A, Marques L, Penders J (2009) Guardians robot swarm exploration and firefighter assistance. In: Workshop on NRS in IEEE/RSJ international conference on Intelligent Robots and Systems (IROS), St Louis, USA

    Google Scholar 

  4. Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm intelligence: from natural to artificial systems. Oxford University Press, New York

    MATH  Google Scholar 

  5. Beni G (2004) From swarm intelligence to swarm robotics. In: Proceedings of the swarm robotics workshop, Heidelberg, Germany, pp 1–9

    Google Scholar 

  6. 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, Nagoya, pp 39–43

    Google Scholar 

  7. Tillett J, Rao TM, Sahin F, Rao R, Brockport S (2005) Darwinian particle swarm optimization. In: Proceedings of the 2nd Indian international conference on artificial intelligence, Pune, pp 1474–1487

    Google Scholar 

  8. Rocha R, Dias J, Carvalho A (2005) Cooperative multi-robot systems: a study of visionbased 3-D mapping using information theory. Robot Auton Syst 53(3–4):282–311

    Article  Google Scholar 

  9. Couceiro MS, Rocha RP, Ferreira NMF (2011) A novel multi-robot exploration approach based on particle swarm optimization algorithms. In: Proceedings of the IEEE international symposium on Safety, Security, and Rescue Robotics, SSRR2011, Kyoto, Japan, pp 327–332

    Google Scholar 

  10. Couceiro MS, Rocha RP, Ferreira NMF (2011) Ensuring Ad Hoc connectivity in distributed search with Robotic Darwinian Swarms. In: Proceedings of the IEEE international symposium on Safety, Security, and Rescue Robotics, SSRR2011, Kyoto, Japan, pp 284–289

    Google Scholar 

  11. Lee JS, Su YW, Shen CC (2007) A comparative study of wireless protocols: bluetooth, UWB, ZigBee, and Wi-Fi. In: Proceedings of the 33rd annual conference of the IEEE Industrial Electronics Society, Vigo, pp 46–51

    Google Scholar 

  12. Pedrosa AC, Gama SMA (2004) Introdução Computacional à Probabilidade e Estatística. Porto Editora, Portugal

    Google Scholar 

  13. Maroco J (2010) Análise Estatística com utilização do SPSS. Edições Silabo, Lisboa

    Google Scholar 

  14. Pallant J (2011) SPSS survival manual. Kindle Edition (ed) 4th edn. Open University Press, Maidenhead

    Google Scholar 

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Acknowledgments

This work was supported by a PhD scholarship (SFRH/BD /73382/2010) granted to the first author by the Portuguese Foundation for Science and Technology (FCT) and the Institute of Systems and Robotics (ISR) also under regular funding by FCT.

Author information

Authors and Affiliations

  1. Institute of Systems and Robotics, University of Coimbra, Pinhal de Marrocos - Polo II, 3030-290, Coimbra, Portugal

    Micael S. Couceiro & Rui P. Rocha

  2. RoboCorp, Department of Electrical Engineering, Engineering Institute of Coimbra, Rua Pedro Nunes, Quinta da Nora, 3030-199, Coimbra, Portugal

    Micael S. Couceiro & Nuno M. F. Ferreira

  3. Instituto de Telecomunicações (Covilhã), Coimbra College of Education, Rua Dom João III – Solum, 3030-329, Coimbra, Portugal

    Fernando M. L. Martins

  4. RoboCorp, Faculty of Sport Sciences and Physical Education, University of Coimbra, Estádio Universitário – Pavilhão III Stª Clara, 3030-156, Coimbra, Portugal

    Filipe Clemente

Authors
  1. Micael S. Couceiro
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  2. Fernando M. L. Martins
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  3. Filipe Clemente
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  4. Rui P. Rocha
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  5. Nuno M. F. Ferreira
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Corresponding author

Correspondence to Micael S. Couceiro .

Editor information

Editors and Affiliations

  1. Computer Science Department, Polytechnique Institute of Porto, Rua Dr. Bernardino de Almeida 431, Porto, 4200-072, Portugal

    Ana Madureira

  2. Electrical and Engineering Department, Polytechnique Institute of Porto, Rua Dr. Bernardino de Almeida 431, Porto, 4200-072, Portugal

    Cecilia Reis

  3. , Department of Computer Science and Syste, Polytechnique Institute of Coimbra, Rua Pedro Nunes - Quinta da Nora, Coimbra, 3030-199, Portugal

    Viriato Marques

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Couceiro, M.S., Martins, F.M.L., Clemente, F., Rocha, R.P., Ferreira, N.M.F. (2013). Towards a Further Understanding of the Robotic Darwinian PSO. In: Madureira, A., Reis, C., Marques, V. (eds) Computational Intelligence and Decision Making. Intelligent Systems, Control and Automation: Science and Engineering, vol 61. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4722-7_2

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  • DOI: https://doi.org/10.1007/978-94-007-4722-7_2

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-4721-0

  • Online ISBN: 978-94-007-4722-7

  • eBook Packages: EngineeringEngineering (R0)

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