Novel approach to visual robot control
In this paper a new control scheme for a robot manipulator based on visual information is proposed. The control system determines the position and orientation of the robot gripper in order to achieve desired grasping relation between the gripper and a 3D object. The proposed control scheme consists of two distinct stages: (1) Learning stage, in this stage the robot system reconstructs a 3D geometrical model of a presented unknown object within a class of objects (polyhedra), by integrating information from an image sequence obtained from a camera mounted on the robot manipulator (eye-in-hand). This model is represented by a set of 3D line segments and denoted as a reference model. The robot is also taught desired grasping relation by manual guidance. (2) Execution stage, in this stage the robot system reconstructs a 3D model of the arbitrarily placed 3D object. This model is denoted as an observed model. Then, the necessary position and orientation of its gripper is determined based on estimated 3D displacement between the reference and observed models. Further, the basic algorithm is extended to handle multiple objects manipulation and recognition. The performance of the proposed algorithms has been tested on the real robot system and the experimental results are presented.