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Abstract-The Atomic Force Microscope (AFM) is one of the most versatile tools in nanotechnology. For control engineers this instrument is particularly interesting, since its ability to image the surface of a sample is entirely dependent upon the use of a feedback loop. This paper will present a tutorial on the control of AFMs. We take the reader on a walk around the control loop and discuss each of the individual technology components. The major imaging modes are described from a controls perspective and recent advances geared at increasing the performance of these microscopes are highlighted.

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Abstract-We present a computational framework for automatic deployment of a robot from a temporal logic specification over a set of properties of interest satisfied at the regions of a partitioned environment. We assume that, during the motion of the robot in the environment, the current region can be precisely determined, while due to sensor and actuation noise, the outcome of a control action can only be predicted probabilistically. Under these assumptions, the deployment problem translates to generating a control strategy for a Markov Decision Process (MDP) from a temporal logic formula. We propose an algorithm inspired from probabilistic Computation Tree Logic (PCTL) model checking to find a control strategy that maximizes the probability of satisfying the specification. We illustrate our method with simulation and experimental results.

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