An approach to realize learning calibration-free stereo vision-based robot for manipulating objects is introduced. It allows a robot gather experiences through interaction with the world and continuously improve its performance based on the collected experiences. It uses a direct transition from image coordinates to motor control commands, but no world coordinates and no inverse perspective or kinematic transformations. The approach has been tested in real-world experiences on an uncalibrated vision-guided manipulator with five degrees of freedom to grasp a variety of differently shaped objects.

An approach to control vision-guided robots is introduced. It allows searching and grasping differently shaped objects that may be located anywhere in the robot's work space, even not visible in the initial fields of view of cameras. It eliminates the need for a calibration of the robot and of the vision system, it uses no world coordinates and no inverse perspective or kinematic transformations, and it comprises an automatic adaptation to changing parameters. The approach has been implemented on a calibration-free vision-guided manipulator with five degrees of freedom (DOF) and was evaluated in real-word experiments.

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.