Abstract
This paper presents, a novel decentralized control strategy, named Triangular Formation Algorithm (TFA), for a swarm of simple robots. The TFA is a local interaction strategy which basically makes three neighboring robots to form a regular triangular lattice. This strategy requires minimal conditions for robots and it can be easily realized with real robots. The TFA is executed by every member of the swarm asynchronously. For swarm obstacle avoidance, a simplified artificial physical model is introduced to work with the TFA. Simulation results showed that the global behaviors of swarm such as aggregation, flocking and obstacle avoidance in an unknown environment can be achieved using the TFA and obstacle avoidance mechanism.
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References
Bayindir, L., Şahin, E.: A review of studies in swarm robotics. Turk. J. Elec. Engin. 15(2), 115–147 (2007)
Şahin, E.: Swarm robotics: from sources of inspiration to domains of application. In: Şahin, E., Spears, W.M. (eds.) Swarm Robotics 2004. LNCS, vol. 3342, pp. 10–20. Springer, Heidelberg (2005)
Schmickl, T., Möslinger, C., Crailsheim, K.: Collective perception in a robot swarm. In: Şahin, E., Spears, W.M., Winfield, A.F.T. (eds.) SAB 2006 Ws 2007. LNCS, vol. 4433, pp. 144–157. Springer, Heidelberg (2007)
Shaw, E.: The schooling of fishes. Sci. Am. 206, 128–138 (1962)
Reynolds, C.W.: Flocks, herds, and schools: a distributed behavioral model. Computer Graphics 21(4), 25–34 (1987)
Correll, N., Cianci, C., Raemy, X., Martinoli, A.: Self-organized embedded sensor/actuator networks for “smart” turbines”. In: The IEEE/RSJ International Conference on Intelligent Robots and Systems Workshop on Network Robot System: Toward intelligent robotic systems integrated with environments, IEEE Press, Los Alamitos (2006)
Chong, C.Y., Kumar, S.P.: Sensor networks: evolution, opportunities, and challenges. Proceedings of the IEEE 91(8), 1247–1256 (2003)
Godwin, M.F., Spry, S.C., Hedrick, J.K.: Distributed system for collaboration and control of UAV groups: experiments and analysis. In: Grundel, D., Murphey, R., Pardalos, P., Prokopyev, O. (eds.) Cooperative Systems. LNEMS, vol. 588, pp. 139–156. Springer, Heidelberg (2007)
Gustafson, E.H., Lollini, C.T., Bishop, B.E., Wick, C.E.: Swarm technology for search and rescue through multi-sensor multi-viewpoint target identification. In: The 37th Southeastern Symposium on System Theory, pp. 352–356. IEEE Press, Los Alamitos (2005)
Bahceci, E., Soysal, O., Sahin, E.: A review: pattern formation and adaptation in multi-robot systems. Technical Report CMU-RI-TR-03-43, Carnegie Mellon University, Pittsburgh, PA, USA (2003)
Egerstedt, M., Hu, X.: Formation constrained multi-agent control. IEEE Transaction on Robotics and Automation 17(6), 947–951 (2001)
Koo, T.J., Shahruz, S.M.: Formation of a group of unmanned aerial vehicles. In: The American Control Conference (ACC), vol. 1, pp. 69–74. IEEE Press, Los Alamitos (2001)
Balch, T., Hybinette, M.: Behavior-based coordination of large scale robot formations. In: The 4th International Conference on Multiagent Systems (ICMAS), pp. 363–364. IEEE Press, Los Alamitos (2000)
Balch, T., Hybinette, M.: Social potentials for scalable multi-robot formations. In: The IEEE International Conference on Robotics and Automation (ICRA), vol. 1, pp. 73–80. IEEE Press, Los Alamitos (2000)
Baras, J.S., Tan, X., Hovareshti, P.: Decentralized control of autonomous vehicles. In: 42nd IEEE Conference on Decision and Control, pp. 1532–1537. IEEE Press, Los Alamitos (2003)
Kim, D.H., Wang, H., Shin, S.: Decentralized control of autonomous swarm systems using artificial potential function-analytical design guidelines. J. Intell. Robot Syst. 45, 36–394 (2006)
Spears, W.M., Spears, D.F., Heil, R., Kerr, W., Hettiarachchi, S.: An overview of physicomimetics. In: Şahin, E., Spears, W.M. (eds.) Swarm Robotics 2004. LNCS, vol. 3342, pp. 84–97. Springer, Heidelberg (2005)
Spears, W., Spears, D., Hamann, J., Heil, R.: Distributed, physics-based control of swarms of vehicles. Autonomous Robots 17, 137–162 (2004)
Shucker, B., Bennett, J.K.: Scalable Control of Distributed Robotic Macrosensors. In: The 7th International Symposium on Distributed Autonomous Robotic Systems (DARS 2004). IEEE Press, Los Alamitos (2004)
Shucker, B., Bennett, J.K.: Virtual Spring Mesh Algorithms for Control of Distributed Robotic Macrosensors. Technical report CU-CS-996-05, Department of Computer Science, University of Colorado at Boulder (2005)
Lee, G., Chong, N.Y.: Decentralized formation control for a team of anonymous mobile robots. In: The 6th Asian Control Conference, pp. 971–976. IEEE Press, Los Alamitos (2006)
Lee, G., Chong, N.Y.: Flocking controls for swarms of mobile robots inspired by fish schools. In: Lazinica, A. (ed.) Recent advances in multi robot systems, I-Tech Education and Publishing, Vienna, Austria (2008)
Klein, J.: Breve: a 3D simulation environment for the simulation of decentralized systems and artificial life. In: Artificial Life VIII, the 8th International Conference on the Simulation and Synthesis of Living Systems, MIT Press, Cambridge (2002), http://www.spiderland.org/breve
Yang, Y., Xiong, N., Chong, N.Y., Défago, X.: A decentralized and adaptive flocking algorithm for autonomous mobile robots. In: The 3rd International Conference on Grid and Pervasive Computing Workshops, pp. 262–268. IEEE Press, Los Alamitos (2008)
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Li, X., Ercan, M.F., Fung, Y.F. (2009). A Triangular Formation Strategy for Collective Behaviors of Robot Swarm. In: Gervasi, O., Taniar, D., Murgante, B., Laganà, A., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2009. ICCSA 2009. Lecture Notes in Computer Science, vol 5592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02454-2_70
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DOI: https://doi.org/10.1007/978-3-642-02454-2_70
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