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Morphogenetic Self-Organization of Collective Movement without Directional Sensing

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Advances in Autonomous Robotics Systems (TAROS 2014)

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Abstract

In this paper, we present a morphogenetic approach to self-organized collective movement of a swarm. We assume that the robots (agents) do not have global knowledge of the environment and can communicate only locally with other robots. In addition, we assume that the robots are not able to perform directional sensing. To self-organize such systems, we adopt here a simplified diffusion mechanism inspired from biological morphogenesis. A guidance mechanism is proposed based on the history of morphogen concentrations. The division of labor is achieved by type differentiation to allocate different tasks to different type of robots. Simulations are run to show the efficiency of the proposed algorithm. The robustness of the algorithm is demonstrated by introducing an obstacle into the environment and removing a subset of robots from the swarm.

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References

  1. Navarro, I., Matia, F.: A Survey of Collective Movement of Mobile Robots. Int. J. Adv. Robot. Sys. 10, 1–9 (2013)

    Google Scholar 

  2. Couceiro, M.S., Portugal, D., Rocha, R.P.: A Collective Robotic Architecture in Search and Rescue Scenarios. In: 28th Annual ACM Symposium on Applied Computing, pp. 64–69. ACM Press, New York (2013)

    Chapter  Google Scholar 

  3. Stirling, T., Wischmann, S., Floreano, D.: Energy-efficient indoor search by swarms of simulated flying robots without global information. Swarm Intell. 4, 117–143 (2010)

    Article  Google Scholar 

  4. Shen, W.-M., Will, P., Galstyan, A.: Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms. Auton. Robot. 17, 93–105 (2004)

    Article  Google Scholar 

  5. Guoa, H., Meng, Y., Jin, Y.: A Cellular Mechanism For Multi-Robot Construction Via Evolutionary Multi-Objective Optimization of a Gene Regulatory Network. BioSystems 98, 193–203 (2009)

    Article  Google Scholar 

  6. Sayama, H.: Robust Morphogenesis of Robotic Swarms. IEEE Comput. Intell. Mag. 5, 43–49 (2010)

    Article  Google Scholar 

  7. Guo, H., Jin, Y., Meng, Y.: A Morphogenetic Framework for Self-Organized Multirobot Pattern Formation and Boundary Coverage. ACM Trans. Auton. Adap. Syst. 7, Article No. 15 (2012)

    Google Scholar 

  8. Jin, Y., Guo, H., Meng, Y.: A Hierarchical Gene Regulatory Network for Adaptive Multirobot Pattern Formation. IEEE Trans. Syst., Man, Cybern.,Syst. 42, 805–816 (2012)

    Article  Google Scholar 

  9. Mamei, M., Vasirani, M., Zambonelli, F.: Experiments of Morphogenesis in Swarms of Simple Mobile Robots. Appl. Artif. Intell. 18, 903–919 (2004)

    Article  Google Scholar 

  10. Ikemoto, Y., Hasegawa, Y., Fukuda, T., Matsuda, K.: Gradual Spatial Pattern Formation of Homogeneous Robot Group. Inf. Sci. 171, 431–445 (2005)

    Article  Google Scholar 

  11. Sayama, H.: Swarm Chemistry. Artif. Life. 15, 105–114 (2009)

    Article  Google Scholar 

  12. Eyiyurekli, M., Bai, L., Lelkes, P.I., Breen, D.E.: Chemotaxis-based Sorting of Self-Organizing Heterotypic Agents. In: 25th ACM Symposium on Applied Computing, Sierre, Switzerland, pp. 1315–1322 (2010)

    Google Scholar 

  13. Davies, J.: Mechanisms of Morphogenesis. Elsevier Academic Press, Amsterdam (2005)

    Google Scholar 

  14. Ho, C.S., Nguyen, Q.H., Ong, Y.-S., Chen, X.: Autonomous Multi-agents in Flexible Flock Formation. In: Boulic, R., Chrysanthou, Y., Komura, T. (eds.) MIG 2010. LNCS, vol. 6459, pp. 375–385. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  15. Navarro, I., Matia, F.: A Framework for the Collective Movement of Mobile Robots Based on Distributed Decisions. Robot. Auton. Syst. 59, 685–697 (2011)

    Article  Google Scholar 

  16. Rubenstein, M., Christian, A., Radhika, N.: A Low Cost Scalable Robot System for Collective Behaviors. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3293–3298. Computer Society Press of the IEEE, Saint Paul (2012)

    Google Scholar 

  17. Shvartsman, S.Y., Coppey, M., Berezhkovskii, A.M.: Dynamics of Maternal Morphogen Gradients in The Drosophila Embryo. Curr. Opin. Genet. Dev. 18, 342–347 (2008)

    Article  Google Scholar 

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Ramezan Shirazi, A., Oh, H., Jin, Y. (2014). Morphogenetic Self-Organization of Collective Movement without Directional Sensing. In: Mistry, M., Leonardis, A., Witkowski, M., Melhuish, C. (eds) Advances in Autonomous Robotics Systems. TAROS 2014. Lecture Notes in Computer Science(), vol 8717. Springer, Cham. https://doi.org/10.1007/978-3-319-10401-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-10401-0_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10400-3

  • Online ISBN: 978-3-319-10401-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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