Stochastic trajectory planning and navigation for AFM based nano robotic manipulation

AFM based nano robotics uses the tip to perform observing and maneuvering with high resolution and accuracy. The tip position uncertainties in the task space due to the PZT nonlinearity and thermal drift is compensated by using the landmarks existing in the task region. This method can detect and control the accuracy of the relative position between AFM tip and the interest object. However, as for the complex situations including several features and seldom features in the task regions, the tip trajectory need to be planned, and its position accuracy is required to be retained in the allowance. So this paper proposes the stochastic trajectory planning and navigation based on local scan by using the shortest path according to the tip motion model. The observation distance is defined and landmark adjacency matrix is established for designing the observed landmarks. Also the landmark domain is defined to actively configure the feature. The simulation and experimental results are performed to illustrate the efficiency of the proposed method