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In this paper, a decoupling algorithm based on the RBF (radical basis function) network is proposed. Compared to the Levenberg-Marquardt (L-M) algorithm and CMA-ES algorithm, numerical experiments show that the decoupling algorithm based on the radial basis function network is of higher performance on both accuracy and time complexity, which makes the(More)
Conductive rubber material has been widely investigated as a sensor and transducer material due to its high piezoresistive, conductive properties. In this paper, we report on a flexible tactile sensor which is based on conductive rubber filled with carbon black. Firstly, a physical model related linear elasticity mechanics and franklinic analogue method is(More)
A decoupling method based on radical basis function neural network (RBFNN) for a novel three-dimensional force flexible tactile sensor is presented in this paper. A numerical model of the tactile sensor is built through finite element analysis, which simulates the mapping between three-dimensional force applied on top surface of the sensor and deformation(More)
A preliminary numerical model of a three-dimensional tactile sensor based on FEA (finite element analysis) is proposed. The mapping between the resistances and the deformation of the simplified tactile sensor is established by ANSYS™, which will provide useful information to improve the design of the sensor. A decoupling algorithm based on the RBF(More)
This paper proposes a decoupling method for a novel tactile sensor based on improved Back Propagation Neural Network (BPNN). In the numerical experiments, the number of hidden layer nodes of the BPNN is optimized and k-fold-cross-validation (k-CV) method is also applied to construct the dataset. Furthermore, information of the tactile sensor array at(More)
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