Title :
Robot end-effector 2D visual positioning using neural networks
Author :
Yang, Yan-xi ; Liu, Ding ; Liu, Han
Author_Institution :
Xi´´an Univ. of Technol., China
Abstract :
A visual positioning controller of robot manipulator system with a camera in hand is presented in this paper, where a feedforward neural network is involved to drive the end-effector of manipulator to the desired position instead of the proportional controller. In this case, the visual sensory input is directly translated to world actuator domain. Simulation results show that this method can drive the static positioning error to zero quickly and keep good dynamic response at the same time compared with proportional control law.
Keywords :
end effectors; feedforward neural nets; position control; robot vision; 2D visual positioning controller; actuator domain; camera; feedforward neural network; proportional controller; robot end effector; robot manipulator system; static positioning error; visual sensory input; Actuators; Cameras; Control systems; Feedforward neural networks; Manipulator dynamics; Neural networks; Proportional control; Robot control; Robot sensing systems; Robot vision systems;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1260075
