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Collective Tasks for a Flock of Robots Using Influence Factor

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Abstract

In this paper, a form of steering a swarm of robots is presented using behavior local rules that depends on four parameters. These parameters are related with a general model of the behavior of social animals called repulsion, attraction orientation and influence. By simulations, a kinematic and dynamical math models of robots were made for testing its performance as a swarm and to know the impact of the parameters considering two tasks of location and navigation considering aggregation and flocking as a minimum condition that the swarm must have. An implementation was made building a flock of simple robots with hardware and software limitations. Some statistics to measure the performance of the swarm considering its covered area are proposed and analyze the impact of parameters on the swarm. Results of simulation are similar to the implementations as expected. The proposed behavior rules based on repulsion, attraction and orientation determine the formation of the swarm or the flock and influence emphasizes the principal task; in other words, associate a specific task with a specific perception or signal.

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References

  1. Linda, O., Manic, M.: Fuzzy manual control of multi-robot system with built-in swarm behavior. In: 2nd Conference on Human System Interactions, 2009. HSI ’09, pp. 4–9 (May 2009)

  2. Tan, Y., yang Zheng, Z.: Research advance in swarm robotics. Def. Technol. 9(1), 18–39 (2013)

    Article  Google Scholar 

  3. Fine, B., Shell, D.: Unifying microscopic flocking motion models for virtual, robotic, and biological flock members. Auton. Robot. 35(2-3), 195–219 (2013)

    Article  Google Scholar 

  4. Moeslinger, C., Schmickl, T., Crailsheim, K.: Emergent flocking with low-end swarm robots Dorigo, M., Birattari, M., Di Caro, G., Doursat, R., Engelbrecht, A., Floreano, D., Gambardella, L., Groß, R., Şahin, E., Sayama, H., Stützle, T. (eds.) . Springer, Berlin (2010)

  5. Moeslinger, C., Schmickl, T., Crailsheim, K.: A minimalist flocking algorithm for swarm robots. In: Kampis, G., Karsai, I., Szathmáry, E. (eds.) Advances in Artificial Life. Darwin Meets von Neumann, vol. 5778 of Lecture Notes in Computer Science, pp. 375–382. Springer, Berlin (2011)

  6. Brutschy, A., Garattoni, L., Brambilla, M., Francesca, G., Pini, G., Dorigo, M., Birattari, M.: The tam: abstracting complex tasks in swarm robotics research. Swarm Intell. 9(1), 1–22 (2015)

    Article  Google Scholar 

  7. Couceiro, M.S., Vargas, P.A., Rocha, R.P., Ferreira, N.M.: Benchmark of swarm robotics distributed techniques in a search task. Robot. Auton. Syst. 62(2), 200–213 (2014)

    Article  Google Scholar 

  8. Ducatelle, F., Di Caro, G.A., Gambardella, L.M.: Cooperative self-organization in a heterogeneous swarm robotic system. In: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, GECCO ’10, (New York, NY, USA), pp. 87–94 ACM (2010)

  9. Linda, O., Manic, M.: Fuzzy force-feedback augmentation for manual control of multirobot system. IEEE Trans. Ind. Electron. 58, 3213–3220 (2011)

    Article  Google Scholar 

  10. Bayι nd ιr, L.: A review of swarm robotics tasks. Neurocomputing 172, 292–321 (2016)

    Article  Google Scholar 

  11. Brambilla, M., Ferrante, E., Birattari, M., Dorigo, M.: Swarm robotics: A review from the swarm engineering perspective. Swarm Intell. 7(1), 1–41 (2013)

    Article  Google Scholar 

  12. Reynolds, C.W.: Flocks, herds and schools: A distributed behavioral model. In: Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, Siggraph’87, (New York, NY, USA), pp. 25–34 ACM (1987)

  13. Couzin, I.D., Krause, J., James, R., Ruxton, G.D., Franks, N.R.: Collective memory and spatial sorting in animal groups. J. Theor. Biol. 218(1), 1–11 (2002)

    Article  MathSciNet  Google Scholar 

  14. Pac, M., Erkmen, A., Erkmen, I.: Control of robotic swarm behaviors based on smoothed particle hydrodynamics. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007, pp. 4194–4200 (2007)

  15. Pimenta, L., Pereira, G., Michael, N., Mesquita, R., Bosque, M., Chaimowicz, L., Kumar, V.: Swarm coordination based on smoothed particle hydrodynamics technique. IEEE Trans. Robot. 29, 383–399 (2013)

    Article  Google Scholar 

  16. Kira, Z., Potter, M.: Exerting human control over decentralized robot swarms. In: 4th International Conference on Autonomous Robots and Agents, 2009. ICARA 2009, pp. 566–571 (2009)

  17. Bashyal, S., Venayagamoorthy, G.: Human swarm interaction for radiation source search and localization. In: Swarm Intelligence Symposium, 2008. SIS 2008. IEEE, pp. 1–8 (2008)

  18. Nnd Newman, P.Ro.ay, Srinivasa, S.: What types of interactions do bio-inspired robot swarms and flocks afford a human? p. 504. MIT Press, Cambridge (2013)

    Google Scholar 

  19. Jung, S.-Y., Goodrich, M.: Multi-robot perimeter-shaping through mediator-based swarm control. In: 16th International Conference on Advanced Robotics (ICAR), 2013, pp. 1–6 (2013)

  20. Ducatelle, F., Di Caro, G., Förster, A., Bonani, M., Dorigo, M., Magnenat, S., Mondada, F., O’Grady, R., Pinciroli, C., Rétornaz, P., Trianni, V., Gambardella, L.: Cooperative navigation in robotic swarms. Swarm Intell. 8(1), 1–33 (2014)

    Article  Google Scholar 

  21. Martinez, F., Jacinto, E., Acero, D.: Brownian motion as exploration strategy for autonomous swarm robots. In: IEEE International Conference on Robotics and Biomimetics (ROBIO), 2012, pp. 2375–2380 (2012)

  22. Pashna, M., Yusof, R., Rahmani, R.: Oil spill trajectory tracking using swarm intelligence and hybrid fuzzy system. In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014, pp. 1346–1351 (2014)

  23. Junior, L.S., Nedjah, N.: Wave algorithm applied to collective navigation of robotic swarms. Appl. Soft Comput. 157(Supplement C), 698–707 (2017)

    Article  Google Scholar 

  24. Hoshino, S., Takisawa, R., Kodama, Y.: Swarm robotic systems based on collective behavior of chloroplasts. Journal of robotics and mechatronics 29(3), 602–612 (2017)

    Article  Google Scholar 

  25. Mendonca, M., Chrun, I.R., Neves, F., Arruda, L.: A cooperative architecture for swarm robotic based on dynamic fuzzy cognitive maps. Eng. Appl. Artif. Intell. 159(Supplement C), 122–132 (2017)

    Article  Google Scholar 

  26. Stojanovic, V., Nedic, N., Prsic, D., Dubonjic, L.: Optimal experiment design for identification of arx models with constrained output in non-gaussian noise. Appl. Math. Model. 40(13), 6676–6689 (2016)

    Article  MathSciNet  Google Scholar 

  27. Stojanovic, V., Filipovic, V.: Adaptive input design for identification of output error model with constrained output. Circuits Systems Signal Process. 33, 97–113 (2014)

    Article  MathSciNet  Google Scholar 

  28. Filipovic, V., Nedic, N., Stojanovic, V.: Robust identification of pneumatic servo actuators in the real situations. Forsch. Ingenieurwes. 75, 183–196 (2011)

    Article  Google Scholar 

  29. Stojanovic, V., Nedic, N.: A nature inspired parameter tuning approach to cascade control for hydraulically driven parallel robot platform. J. Optim. Theory Appl. 168, 332–347 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  30. Stojanovic, V., Nedic, N., Prsic, D., Dubonjic, L., Djordjevic, V.: Application of cuckoo search algorithm to constrained control problem of a parallel robot platform. The International Journal of Advanced Manufacturing Technology 87, 2497–2507 (2016)

    Article  Google Scholar 

  31. Prsić, D., Nedić, N., Stojanović, V.: A nature inspired optimal control of pneumatic-driven parallel robot platform. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. 231(1), 59–71 (2017)

    Article  Google Scholar 

  32. Bara, A., Dale, S.: Dynamic modeling and stabilization of wheeled mobile robot. In: Proceedings of the 5th WSEAS International Conference on Dynamical Systems and Control, CONTROL’09, (Stevens Point, Wisconsin, USA), pp. 87–92 World Scientific and Engineering Academy and Society (WSEAS) (2009)

  33. Kelly, R., Santibáñez Dávila, V., Loría, A.: Control of Robot Manipulators in Joint Space. Advanced Textbooks in Control and Signal Processing. Springer, London (2005)

    Google Scholar 

  34. Khalil, H.K.: Nonlinear systems. Prentice-Hall, Upper Saddle River (1996)

    Google Scholar 

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Authors and Affiliations

  1. Facultad de Ingenieria Mecanica y Electrica, Universidad Autonoma de Nuevo Leon, Ave. Universidad S/N, Cd. Universitaria, San Nicolas de los Garza, N.L. CP 66455, Mexico

    Erick Ordaz-Rivas, Angel Rodriguez-Liñan, Mario Aguilera-Ruíz & Luis Torres-Treviño

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  1. Erick Ordaz-Rivas
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  2. Angel Rodriguez-Liñan
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  3. Mario Aguilera-Ruíz
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  4. Luis Torres-Treviño
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Correspondence to Luis Torres-Treviño.

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Ordaz-Rivas, E., Rodriguez-Liñan, A., Aguilera-Ruíz, M. et al. Collective Tasks for a Flock of Robots Using Influence Factor. J Intell Robot Syst 94, 439–453 (2019). https://doi.org/10.1007/s10846-018-0941-2

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  • DOI: https://doi.org/10.1007/s10846-018-0941-2

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