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Tactile sensor with good flexibility is a promising candidate for artificial skin of intelligent robots. Some specific structures and models have been proposed to realize sensing of 3-demensional tactile forces. Due to the natural couple properties of these sensor models, decoupling has become an obstacle on the road to practical sensors. In this paper, we start from an elastic mechanics model which...
This paper proposes two decoupling methods for a flexible tactile sensor, improved back propagation neural network (BPNN) and radical basis function neural network (RBFNN). 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. Information of the tactile sensor array at different scales...
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