Virtual reality and high-accuracy vision feedback as key information for microrobot telemanipulation

As microsystems and micro structures become smaller, it is necessary to build a micro robot ((mu) -robot) capable of manipulating these systems and structures. The movements and positions of the robot have to be controlled and guided. The first part of our project was to develop a real time 3D computer graphics (virtual reality) environment man-machine interface to guide the newly developed robot. Secondly, we calibrated the camera and microscope system to evaluate measurement techniques to verify robots' position in the region of interest (workspace) at a sub micron accuracy. Our latest developments of using a high resolution vision system as well as the controlling strategy of a new type of micro robot are discussed. The simple and compact design of the robot is believed to be promising in the micro robotics field. Stepping motion allows speeds up to 4 mm/s. Resolution smaller than 10 nm is achievable. Using high resolution camera calibration, passive auto focus algorithms and 2D object recognition the position of the robot can be controlled in the 3D workspace to guide the micro assembly. We focus on the vision system and on the virtual reality interface of the complex system. Basically the user interacts with the virtual 3D microscope and sees the micro- robot as if he is looking through a real microscope. He is able to simulate the assembly of the missing parts, e.g. parts of a micromotor, beforehand in order to verify the assembly manipulation steps such as measuring, moving the table to the right position, or performing the manipulation. Micro manipulation the in form of a teleoperation is then performed by the real robot-unit and the position is controlled by vision in an internal loop. Results have shown, that a guided manipulation with sub micron absolute accuracy of the robot can be achieved. A key idea of this approach is to use the intuitiveness of immersed vision to perform robotic tasks in an environment where the operator only has access using high performing measurement and visualization systems. Using also the virtual scene exactly reconstructed from the CAD-CAM-databases of the real environment being considered as the a priori knowledge, human observations and computer-vision based techniques improve the robustness and speed of such an application tremendously. Robust computer vision is used for 3D micro- object recognition and very promising for micro assembly, microsystem measurement and quality assurance of micro fabrication techniques.