Abstract
In this paper, a feedforward neural network is trained towards the generalisation of the inverse kinematics of a 3R metamorhic manipulator with one pseudojoint. A two hidden-layered network is trained with data produced by several anatomies of the metamorphic manipulator and tested to an unforeseen anatomy. The data are separated to aspects per anatomy and combined to one training set. Various configurations of the network is trained using the Levenberg-Marquardt backpropagation method and the best of them is derived. As it will be shown the derived network can achieve very low generalisation errors.
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Acknowledgement
Part of this research has been financially supported by General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI) (Code: 1184).
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Tzivaridis, M., Moulianitis, V.C., Aspragathos, N.A. (2020). Approximation of Inverse Kinematic Solution of a Metamorphic 3R Manipulator with Multilayer Perceptron. In: Berns, K., Görges, D. (eds) Advances in Service and Industrial Robotics. RAAD 2019. Advances in Intelligent Systems and Computing, vol 980. Springer, Cham. https://doi.org/10.1007/978-3-030-19648-6_6
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