Stereo Vision-Based Object Classification
Abstract
A novel concept
for recognition and classification of differently formed objects is introduced.
It can be used for manipulating objects by uncalibrated vision-guided
manipulators. The object recognition is achieved according to an
object-oriented and model-based approach. The task is decomposed into several
largely independent modules, and each module is responsible for a limited
subtask. The emphasis in this article is on the object classification. It is
achieved by observing directly the object appearance in real-time images
without precise quantitative knowledge about the manipulated objects.
The approach was
evaluated and demonstrated in real-word experiments on an uncalibrated
vision-guided manipulator with five degrees of freedom (DOF) for recognition,
classification and manipulation of a variety of differently shaped objects in
nearly arbitrary orientations and positions anywhere in the robot's 3-D work
space.
Keywords: Calibration-Free Robot Control, Object Classification, Object Grasping, Object Recognition, Robot Vision.