Sensor Referenced Real-Time Videolization of Atomic Force Microscopy for Nanomanipulations

The main problem of atomic force microscopy (AFM)-based nanomanipulation is the lack of real-time visual feedback. Although this problem has been partially solved by virtual reality technology, the faulty display caused by random drift and modeling errors in the virtual reality interface are still limiting the efficiency of the AFM-based nanomanipulation. Random drift aroused from an uncontrolled manipulation environment generates a position error between the manipulation coordinate and the true environment. Modeling errors due to the uncertainties of the nanoenvironment often result in displaying a wrong position of the object. Since there is no feedback to check the validity of the display, the faulty display cannot be detected in real time and leads to a failed manipulation. In this paper, a real-time fault detection and correction (RFDC) method is proposed to solve these problems by using the AFM tip as an end effector as well as a force sensor during manipulation. Based on the interaction force measured from the AFM tip, the validity of the visual feedback is monitored in real time by the developed Kalman filter. Once the faulty display is detected, it can be corrected online through a quick local scan without interrupting manipulation. In this way, the visual feedback keeps consistent with the true environment changes during manipulation, which makes it possible for several operations to finish without an image scan in between. The theoretical study and the implementation of the RFDC method are elaborated. Experiments of manipulating nanomaterials including nanoparticles and nanorods have been carried out to demonstrate its effectiveness and efficiency.