Title :
Neural network-Based hand posture control of a humanoid Robot Hand
Author :
Huluta, Emanuil ; Da Silva, Rafael Ferreira ; de Oliveira, Thiago Eustaquio Alves
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada
Abstract :
This paper presents a novel method to provide Neural Network Based Control of a Multi-finger Robot Hand. There are several challenges known from the literature that researchers are facing when they are trying to produce a human-like trainable robotic hand due to the complexity of building it and controlling its 3D movement. The authors of this article are providing an improved solution to this problem by developing a framework that enables easy training and control of a Robotic Hand by using Artificial Neural Networks.
Keywords :
dexterous manipulators; motion control; neurocontrollers; robot vision; 3D movement control; artificial neural networks; human-like trainable robotic hand; humanoid robot hand; multifinger robot hand; neural network-based hand posture control; Accuracy; Biological neural networks; Robot sensing systems; Thumb; Training; Kinect depth sensor; artificial neural network; dexterous control; hand kinematics; inverse Jacobian; robot hand;
Conference_Titel :
Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2014 IEEE International Conference on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4799-2613-8
DOI :
10.1109/CIVEMSA.2014.6841450
