Abstract
Swarm systems for multiagent control rely on natural models of behavior. Such models both predict simulated natural behavior and provide control instructions to the underlying agents. These two roles can differ when, for example, controlling nonholonomic robots incapable of executing some control suggestions from the system. We consider a simple physicomimetics system and examine the effects of actuation constraint on that system in terms of its ability to stabilize in regular formations, as well as the impact of such constraints on learning control parameters. We find that in the cases we considered, Physicomimetics is surprisingly robust to certain types of actuation constraint.
This work was funded as part of the ARL/HRED project on Team Performance in Human-Agent Collaboration (W911NF-07-R-0001).
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References
Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence. Oxford University Press, Oxford (1999)
Spears, W., Spears, D., Hamann, J., Heil, R.: Distributed, physics-based control of swarms of vehicles. Autonomous Robots 17, 137–162 (2004)
Wiegand, R., Potter, M., Sofge, D., Spears, W.: A generalized graph-based method for engineering swarm solutions to multiagent problems. In: Parallel Problem Solving From Nature, pp. 741–750 (2006)
Zarzhitsky, D., Spears, D., Thayer, D., Spears, W.: A fluid dynamics approach to multi-robot chemical plume tracing. In: Auton. Agents and Multi-Agent Systems, pp. 1476–1477 (2004)
Guibas, L., Stolfi, J.: Primitives for the manipulation of general subdivisions and the computation of voronoi. ACM Trans. Graph. 4(2), 74–123 (1985)
Schwefel, H.P.: Numerical Optimization of Computer Models. Wiley, Chichester (1981)
Reif, J.H., Wang, H.: Social Potential Fields: A Distributed Behavioral Control for Autonomous Robots. Robotics and Autonomous Systems 27(3), 171–194 (1999)
Reynolds, C.: Flocks, herds and schools. Computer Graphics 21, 25–34 (1987)
Ogren, P., Egerstedt, M., Hu, X.: A control lyapunov function approach to multiagent coordination. IEEE Transactions on Robotics and Automation 18, 847–851 (2002)
Nguyen, D., Do, K.: Formation control of mobile robots. International Journal of Computers, Communications and Control I(3), 41–59 (2006)
Lawton, L., Beard, R., Young, B.: A decentralized approach to formation maneuvers. IEEE Transactions on Robotics and Automation 19(6), 933–941 (2003)
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© 2008 Springer-Verlag Berlin Heidelberg
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Ellis, C., Wiegand, R.P. (2008). Actuation Constraints and Artificial Physics Control. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_39
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DOI: https://doi.org/10.1007/978-3-540-87700-4_39
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