Penerbit Universiti Teknikal Malaysia Melaka Press
Abstract
Polishing is a highly skilled manufacturing process with a
lot of constraints and interaction with environment. In general, the purpose
of polishing is to get the uniform surface roughness distributed evenly
throughout part’s surface. In order to reduce the polishing time and cope
with the shortage of skilled workers, robotic polishing technology has been
investigated. This paper studies about vision system to measure surface
defects that have been characterized to some level of surface roughness. The
surface defects data have learned using artificial neural networks to give a
decision in order to move the actuator of arm robot. Force and rotation
time have chosen as output parameters of artificial neural networks. Results
shows that although there is a considerable change in both parameter
values acquired from vision data compared to real data, it is still possible to
obtain surface defects characterization using vision sensor to a certain limit
of accuracy. The overall results of this research would encourage further
developments in this area to achieve robust computer vision based surface
measurement systems for industrial robotic, especially in polishing proces