A Lévy Walk and Firefly Based Multi-Robots Foraging Algorithm

  • Ouarda ZedadraEmail author
  • Antonio Guerrieri
  • Hamid Seridi
  • Giancarlo Fortino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11874)


Foraging constitutes one of the main benchmarks in robotic problems. It is known as the act of searching for objects/tokens and, when found, transport them to one or multiple locations. Swarm intelligence based algorithms have been widely used in foraging problem. The ambient light sensors technology in nowadays robots makes easy using and implementing luminous swarm intelligence-based algorithms such as the Firefly and the Glow-worm algorithms. In this paper, we propose a swarm intelligence-based foraging algorithm called Lévy walk and Firefly Foraging Algorithm (LFFA) which is a hybridizing of the two algorithms Lévy Walk and Firefly Algorithm. Numerical experiments to test the performances are conducted on the ARGoS robotic simulator.


Swarm intelligence Swarm Robotics Lévy Walk Firefly algorithm LFFA algorithm Central Place Foraging (CPF) Multi-Robots Foraging (MRF) 


  1. 1.
    De Rango, F., Palmieri, N.: A swarm-based robot team coordination protocol for mine detection and unknown space discovery. In: 2012 8th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 703–708. IEEE, August 2012.
  2. 2.
    Fioriti, V., Fratichini, F., Chiesa, S., Moriconi, C.: Levy foraging in a dynamic environment - extending the Levy search. Int. J. Adv. Robot. Syst. 12(7), 98 (2015). Scholar
  3. 3.
    Fujisawa, R., Dobata, S.: Lévy walk enhances efficiency of group foraging in pheromone-communicating swarm robots. In: Proceedings of the 2013 IEEE/SICE International Symposium on System Integration, pp. 808–813. IEEE, December 2013.
  4. 4.
    Hassanzadeh, T., Kanan, H.R.: Fuzzy FA: a modified firefly algorithm. Appl. Artif. Intell. 28(1), 47–65 (2014). Scholar
  5. 5.
    Iureva, R.A., Maslennikov, O.S., Komarov, I.I.: Multiagent robotic systems’ ambient light sensor. 10231, 102311J (2017).
  6. 6.
    Katada, Y., Nishiguchi, A., Moriwaki, K., Watakabe, R.: Swarm robotic network using Lévy flight in target detection problem. Artif. Life Robot. 21(3), 295–301 (2016). Scholar
  7. 7.
    Krivonosov, M., Denisov, S., Zaburdaev, V.: Lévy robotics, pp. 1–6 (2016).
  8. 8.
    Lenagh, W., Dasgupta, P.: Levy distributed search behaviors for mobile target locating and tracking. In: Proceedings of the 19th Annual Conference on Behavior Representation in Modeling and Simulation, pp. 103–109 (2010)Google Scholar
  9. 9.
    Palmieri, N., Marano, S.: Discrete firefly algorithm for recruiting task in a swarm of robots. In: Yang, X.-S. (ed.) Nature-Inspired Computation in Engineering. SCI, vol. 637, pp. 133–150. Springer, Cham (2016). Scholar
  10. 10.
    Pina-Garcia, C.A., Gu, D., Hu, H.: A composite random walk for facing environmental uncertainty and reduced perceptual capabilities. In: Jeschke, S., Liu, H., Schilberg, D. (eds.) ICIRA 2011. LNCS (LNAI), vol. 7101, pp. 620–629. Springer, Heidelberg (2011). Scholar
  11. 11.
    Pinciroli, C., et al.: ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intell. 6(4), 271–295 (2012). Scholar
  12. 12.
    Şahin, E., Spears, W.M. (eds.): SR 2004. LNCS, vol. 3342. Springer, Heidelberg (2005). Scholar
  13. 13.
    Şahin, E., Girgin, S., Bayindir, L., Turgut, A.E.: Swarm robotics. In: Blum, C., Merkle, D. (eds.) Swarm Intelligence. Natural Computing Series, pp. 87–100. Springer, Heidelberg (2008). Scholar
  14. 14.
    Sutantyo, D., Levi, P., Moslinger, C., Read, M.: Collective-adaptive Lévy flight for underwater multi-robot exploration. In: 2013 IEEE International Conference on Mechatronics and Automation, pp. 456–462. IEEE, August 2013.
  15. 15.
    Sutantyo, D.K., Kernbach, S., Levi, P., Nepomnyashchikh, V.A.: Multi-robot searching algorithm using Lévy flight and artificial potential field. In: 2010 IEEE Safety Security and Rescue Robotics, pp. 1–6. IEEE, July 2010.
  16. 16.
    Wang, H., et al.: Firefly algorithm with neighborhood attraction. Inf. Sci. 382–383, 374–387 (2017). Scholar
  17. 17.
    Yang, X.-S.: Firefly algorithms for multimodal optimization. In: Watanabe, O., Zeugmann, T. (eds.) SAGA 2009. LNCS, vol. 5792, pp. 169–178. Springer, Heidelberg (2009). Scholar
  18. 18.
    Yang, X.S., Deb, S.: Eagle strategy using Lévy walk and firefly algorithms for stochastic optimization. Stud. Comput. Intell. 284, 101–111 (2010). Scholar
  19. 19.
    Yu, S., Zhu, S., Ma, Y., Mao, D.: A variable step size firefly algorithm for numerical optimization. Appl. Math. Comput. 263, 214–220 (2015). Scholar
  20. 20.
    Zedadra, O., Guerrieri, A., Jouandeau, N., Spezzano, G., Seridi, H., Fortino, G.: Swarm intelligence-based algorithms within IoT-based systems: a review. J. Parallel Distrib. Comput. 122, 173–187 (2018). Scholar
  21. 21.
    Zedadra, O., Idiri, M., Jouandeau, N., Seridi, H., Fortino, G.: Lévy walk-based search strategy: application to destructive foraging. In: Proceedings of the 2018 13th International Symposium on Programming and Systems, ISPS 2018, May 1945, pp. 1–5 (2018).
  22. 22.
    Zedadra, O., Seridi, H., Jouandeau, N., Fortino, G.: An energy-aware algorithm for large scale foraging systems. Scalable Comput. 16(4), 449–466 (2015). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ouarda Zedadra
    • 1
    Email author
  • Antonio Guerrieri
    • 2
  • Hamid Seridi
    • 1
  • Giancarlo Fortino
    • 2
    • 3
  1. 1.LabSTIC, Department of Computer Science8 May 1945 UniversityGuelmaAlgeria
  2. 2.CNR - National Research Council of Italy - Institute for High Performance Computing and Networking (ICAR)RendeItaly
  3. 3.DIMES, Università della CalabriaRendeItaly

Personalised recommendations