Aggressive manuevering of unmanned helicopters: Learning from human based on neural networks

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Abstract

"Teaching by Showing" control of a small helicopter's aggressive maneuvering often needs inner aided controllers based on helicopter's dynamics, which is very complex to identify. In this paper, a neural network based control is proposed, based on the identification of the relationship between the pilot's control and flight states, and it is a model-free control method. Flight test is done in simulation environment based on real flight data. The results show the effectiveness of the neural network based controller for aggressive flight control. © 2013 Springer-Verlag.

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Song, D., Wu, C., Qi, J., & Han, J. (2013). Aggressive manuevering of unmanned helicopters: Learning from human based on neural networks. In Advances in Intelligent Systems and Computing (Vol. 193 AISC, pp. 693–703). Springer Verlag. https://doi.org/10.1007/978-3-642-33926-4_66

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