Robotic Grasping System Using Convolutional Neural Networks

Autor: Pavol Bezák, Pavol Božek, Yury Nikitin
Rok vydání: 2014
Předmět:
Zdroj: American Journal of Mechanical Engineering. 2:216-218
ISSN: 2328-4102
DOI: 10.12691/ajme-2-7-9
Popis: 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..
Databáze: OpenAIRE