Science and Education Publishing American Journal of Mechanical Engineering 2 7 2014 10 15 Robotic Grasping System Using Convolutional Neural Networks 216 218 EN Pavol Bezák Yury Rafailovich Nikitin Pavol Bo?ek Kalashnikov Izhevsk State Technical University, Mechatronic Systems Department, Izhevsk, Russia AJME2014279 10.12691/ajme-2-7-9 2014 09 15 2014 09 29 2014 10 15 Object grasping by robot hands is challenging due to the hand and object modeling uncertainties, unknown contact type and object stiffness properties. To overcome these challenges, the essential purpose is to achieve the mathematical model of the robot hand, model the object and the contact between the object and the hand. In this paper, an intelligent hand-object contact model is developed for a coupled system assuming that the object properties are known. The control is simulated in the Matlab Simulink/ SimMechanics, Neural Network Toolbox and Computer Vision System Toolbox..