Title :
Implementation of a neural network model for control in grasping a moving target
Author :
Lim, Roland S L ; Horan, Peter ; Jarvis, R.A.
Author_Institution :
Dept. of Comput. & Math., Deakin Univ., Geelong, Vic., Australia
Abstract :
An approach to the control of a robot manipulator in grasping a simple moving target with constant speed is presented. A layered neural network architecture-based controller has been developed. It can automatically learn visual motor coordination for the fast reaching movements required in grasping a moving target. A learning scheme known as two-phase learning is described for teaching the skill to the controller. Learning in the controller is achieved through a sequence of trial movements without the presence of a `teacher´. Visual feedback showing the action of the controller is used to adapt it so as to reduce the error between the target and the robot´s gripper
Keywords :
learning (artificial intelligence); manipulators; neural nets; fast reaching movements; layered neural network; moving target; neural network model; robot manipulator; two-phase learning; visual motor coordination; Bismuth; Cameras; Grippers; Intelligent networks; Lattices; Neural networks; Neurofeedback; Neurons; Output feedback; Robot vision systems;
Conference_Titel :
TENCON '92. ''Technology Enabling Tomorrow : Computers, Communications and Automation towards the 21st Century.' 1992 IEEE Region 10 International Conference.
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-0849-2
DOI :
10.1109/TENCON.1992.271902
