Abstract
Self-organized behaviour of distributed autonomous mobile robotic systems is achieved by using pattern formation principles for controlling the robotic units. Several autonomous mobile robotic units are randomly distributed on a plane or in a space, and every unit has to be assigned to one and only one target, a point in the plane or space where some task has to be done. The costs of working on the tasks are given in dependence of the robotic units. Furthermore, the distances between the initial coordinates of the robotic units and the coordinates of the targets are converted into costs. The total costs, i.e., the sum of all costs which have to be incurred, have to be minimized. The proposed algorithm is error resistant and allows sudden changes like a breakdown of some robotic units. The self-organizing behaviour of the robotic units works in analogy to the emergence of rolls or hexagonal patterns in the Bénard problem of fluid dynamics. Simulations of the time-dependent self-organized behaviour of the distributed autonomous mobile robotic system are shown.
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References
Fukuda, T. and T. Ueyama (1994). Cellular Robotics and Micro Robotic Systems. Vol. 10 of World Scientific Series in Robotics and Automated Systems World Scientific.
Fukuda, T., M. Buss, H. Hosokai and Y. Kawauchi (1991). Cell structured robotic system cebot: Control, planning and communication methodsRobotics and Autonomous Systems. 7, 239–248.
Fukuda, T., Y. Kawauchi and H. Asama (1990). Dynamically reconfigurable robotic systems — optimal knowledge allocation for cellular robotic system (cebot). Journal of Robotics and Mechalronics 2 (6), 22–30.
Garey, M. and D. Johnson (1979). Computers and Intractability. Feeman and Company. San Francisco.
Haken, H. (1979). Pattern formation and pattern recognition — an attempt at a synthesis. In: Pattern Formation by Dynamic Systems and Pattern Recognition ( IL Haken, Ed.). pp. 2–13. Springer-Verlag. Heidelberg, Berlin, New York.
Haken, H. (1983a). Advanced Synergetics. Springer-Verlag. Heidelberg, Berlin, New York.
Haken, H. (1983b). Synergetics, An Introduction Springer-Verlag. Heidelberg, Berlin, New York.
Haken, H. (1991). Synergetic Computers and Cognition — A Top-Down Approach to Neural Nets. Springer-Verlag. Heidelberg, Berlin, New York.
Hopficld, J. (1982). Neural networks and physical systems with emergent collective computational abilities. In: Proceedings of the National Academy of Sciences. Vol. 79. pp. 2554–2558.
Kohonen, T. (1984). Self-Organization and Associative Memory. Springer-Verlag. Berlin, Heidelberg, New York.
Molnär, P. (1996a). A microsimulation tool for social force models & pedestrian dynamics. In: Social Science Microsimulation ( K.G. Troitzsch, U. Mueller, G.N. Gilbert and J.E. Doran, Eds.). Springer-Verlag. Berlin, Heidelberg, New York. pp. 155–170.
Molnär, P. (19966). Modellierung und Simulation der Dynamik von Fußgänger-Strömen. PhD thesis. Universität Stuttgart. Verlag Shaker, Aachen.
Müller, B. and J. Reinhardt (1991). Neural Networks — An Introduction. Springer-Verlag. Berlin, Heidelberg, New York.
Papadimitriou, C. and K. Steiglilz (1982). Combinatorial Optimization — Algorithms and Complexity. Prentice-Hall. Englewood Cliffs, New Jersey.
Starke, J. (1996). Cost oriented competing processes — a new handling of assignment problems. In: System Modelling and Optimization (J. Dolezal and J. Fidler, Eds.), pp. 551 — 558. Chapman & Hall. London Glasgow.
Starke, J. (1997). Kombinatorische Optimierung auf der Basis gekoppelter Selektionsgleichungen. PhD thesis. Universität Stuttgart. Verlag Shaker, Aachen.
Starke, J., N. Kubota and T. Fukuda (1995). Combinatorial optimization with higher order neural networks — cost oriented competing processes in flexible manufacturing systems. In: Proceedings of the International Conference on Neural Networks (ICNN’95). Vol. 5. IEEE. pp. 2658 — 2663.
Vanderbauwhede, A. (1989). Center manifolds, normal forms and elementary bifurcations. In: Dynamics Reported (U. Kirchgraber and H. O. Walther, Eds.). Vol. 2. Chap. 4, pp. 89–170. Teubner/John Wiley & Sons. Stuttgart/Chichester, New York, Brisbane.
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Starke, J., Schanz, M., Haken, H. (1998). Self-Organized Behaviour of Distributed Autonomous Mobile Robotic Systems by Pattern Formation Principles. In: Distributed Autonomous Robotic Systems 3. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-72198-4_9
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DOI: https://doi.org/10.1007/978-3-642-72198-4_9
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