Stereo vision-based object classification

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 for recognition, classification and manipulation of a variety of differently shaped objects in nearly arbitrary orientations and positions anywhere in the robot´s 3D work space