Pose estimation of mobile microrobots in a scanning electron microscope - a cross-correlation based approach using ROI's

In this paper, current research towards an automated micro/nano handling station using mobile microrobots is presented. Mobile microrobots with piezo slip-stick actuation and more than one degree of freedom mostly don't have internal pose sensors; therefore a global sensor is needed. This paper focuses on the pose estimation of the mobile microrobots. One possibility for fast pose estimation is the application of video cameras as global sensors. For pose estimation with accuracy even in the nanometer range high resolution sensors are necessary. In consideration of resolution, image acquisition time and depth of focus a Scanning Electron Microscope (SEM) is a powerful sensor for high resolution pose estimation. But the use of a SEM makes high demands on the image processing. High update rates of the pose data for the robot control enforce a short image acquisition time of the SEM images. Hence the image noise increases, because frame averaging or averaging of the detector signal is time consuming. This paper presents a method to calculate the x,y position and the orientation of a micro object in a strongly noised SEM image stream with crosscorrelation in real-time. To make real-time pose estimation possible, only a region-of-interest (ROI) is correlated with the target pattern. The SEM is almost predestined to work with ROI’s, because the scan area of the electron beam can be chosen arbitrarily.