Jeevan J Murthy,Irshad T Y,Harshit P S,Harshith M,Kavya A P,




Swarm Robotics,Social behaviour,Collective behaviour,Robots,


In nature many social animals follow a cooperative behaviour for the common good of their colony. Swarm robotics is a method in which a collection of similar or dissimilar robots follow an organized behaviour pattern to perform some specific tasks. The robots interact and follow simple rules to coordinate a large number of robots. Here we focus on the recent developments in swarm robotics as applied to real world problems. Swarm robotics deals with the defining the rules for the cooperative behaviour and designing, modelling, validating, operating and maintaining the robotics system. Swarm robotics can be classified as per the design and analysis or as per the collective behaviour. The limitations and the future research directions for swarm robotics is also discussed.


I. Ampatzis, C., Tuci, E., Trianni, V., &Dorigo, M.,“Evolution of signaling in a multi-robot system: categorization and communication”, Adaptive Behavior, Vol. 16(1), pp. 5–26, 2008.
II. Bachrach, J., Beal, J., &McLurkin, J.,“Composable continuous-space programs for robotic swarms”, Neural Computing & Applications, Vol. 19(6), pp. 825–847, 2010.
III. Beni, G.,“From swarm intelligence to swarm robotics”, In Lecture notes in computer science:Swarm robotics, Berlin: Springer, Vol. 3342,pp. 1–9, 2005.
IV. Bonabeau, E., Dorigo, M., &Theraulaz, G.,“Swarm intelligence: from natural to artificial systems”, New York: Oxford University Press, 1999.
V. Brambilla, M., Pinciroli, C., Birattari, M., &Dorigo, M.,“Property-driven design for swarm robotics”, In Proceedings of 11th international conference on autonomous agents and multiagent systems (AAMAS 2012), Richland: IFAAMAS, pp. 139–146,2012.
VI. Dorigo, M., & ¸ Sahin, E., Guest editorial. “Autonomous Robots”, Vol. 17, pp. 111–113, 2004.
VII. Dorigo, M., &Birattari, M.,“Swarm intelligence”,Scholarpedia, Vol. 2(9), pp. 1462, 2007.
VIII. Ferrante, E., Brambilla, M., Birattari, M., &Dorigo, M.,“Socially-mediated negotiation for obstacle avoidance in collective transport”, In Springer tracts in advanced robotics: Vol. 83. Proceedings of the international symposium on distributed autonomous robotics systems (DARS 2010), Berlin: Springer, pp. 571–583,2013.
IX. Gazi, V., &Passino, K. M.,“Stability analysis of social foraging swarms: combined effects of attractant/repellent profiles”, In Proceedings of the 41st IEEE conference on decision and control, Piscataway: IEEE Press, Vol. 3, pp. 2848–2853,2002.
X. Pugh, J., &Martinoli, A.,“Parallel learning in heterogeneous multi-robot swarms”, In Proceedings of the IEEE congress on evolutionary computation, Piscataway: IEEE Press, pp. 3839–3846,2007.
XI. Riedmiller, M., Gabel, T., Hafner, R., & Lange, S.,“Reinforcement learning for robot soccer”, Autonomous Robots, Vol. 27(1), pp. 55–73, 2009.
XII. Sahin, E.,“Swarm robotics: from sources of inspiration to domains of application”, In Lecture notes in computer science: Berlin: Swarm robotics, Springer, Vol. 3342. pp. 10–20,2005.
XIII. Seeja G, ArockiaSelvakumar A, Berlin Hency V, “A Survey on Swarm Robotic Modeling, Analysis and Hardware Architecture”, Procedia Computer Science,Vol. 133, pp. 478–485, 2018.
XIV. Soysal, O., & ¸ Sahin, E.,“Probabilistic aggregation strategies in swarm robotic systems”, In Proceedings of the IEEE swarm intelligence symposium, Piscataway: IEEE Press, pp. 325–332,2005.
XV. Spears, W. M., & Spears, D. F.,“Physics-based swarm intelligence”, Berlin: Springer, 2012.
XVI. Waibel, M., Keller, L., &Floreano, D.,“Genetic team composition and level of selection in the evolution of cooperation”, IEEE Transactions on Evolutionary Computation, Vol. 13(3), pp. 648–660, 2009.

View Download