Abstract
Evolutionary Algorithms are now mature optimization tools, especially in a multi-objective context. This ability is used here to help explore, analyse and, on this basis, propose a controller for a complex robotics system: a flapping wings aircraft. A multi-objective optimization is performed to find the best parameters of sinusoidal wings kinematics. Multi-objective algorithms generate a set of trade-off solutions instead of a single solution. The feedback is then potentially more informative in a multi-objective context relative to the one of a single objective setup: the set of trade-off solutions can be analyzed to characterize the studied system. Such an approach is applied to study a simulated flapping wing aircraft. The speed-energy relation is empirically evaluated and the analysis of the relations between the parameters of the kinematics and speed has led, in a further step, to the synthesis of an open-loop controller allowing to change speed during flight.
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Doncieux, S., Hamdaoui, M. (2011). Evolutionary Algorithms to Analyse and Design a Controller for a Flapping Wings Aircraft. In: Doncieux, S., Bredèche, N., Mouret, JB. (eds) New Horizons in Evolutionary Robotics. Studies in Computational Intelligence, vol 341. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18272-3_6
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DOI: https://doi.org/10.1007/978-3-642-18272-3_6
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