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— 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(More)
— We consider the problem of controlling a continuous-time linear stochastic system from a specification given as a Linear Temporal Logic (LTL) formula over a set of linear predicates in the state of the system. We propose a three-step solution. First, we define a polyhedral partition of the state space and a finite collection of controllers, represented as(More)
— In this paper, we present a high-level feedback control algorithm for rapid imaging in atomic force microscopy (AFM). This algorithm is designed for samples which are string-like, such as DNA and biopolymers. The tip control of the microscope is performed in real-time while probing the unknown sample based on feedback from the tip and a model of the(More)
—We discuss the generation of symbolic feedback control sequences for navigating a sparsely-described and uncertain environment, together with the problem of sensing landmarks sufficiently well to make feedback meaningful. We explore the use of a symbolic control approach for mitigating the lack of a detailed map of the environment and for reducing the(More)
— In this paper, we study the performance of a non-raster-scan algorithm for imaging string-like samples in an atomic force microscope. The algorithm yields high-speed imaging through a feedback control law that steers the tip along the sample, thereby reducing the imaging time by eliminating unnecessary measurements. Under simplifying assumptions, we(More)
— We address two key goals pertaining to autonomous mobile robots: one, to develop fast accurate sensory capabilities — at present, the localization of sound sources — and second, the integration of such sensory modules with other robot functions, especially its motor control and navigation. A primary motivation for this work was to devise effective means(More)
—We describe a computational framework for automatic deployment of a robot with sensor and actuator noise from a temporal logic specification over a set of properties that are satisfied by the regions of a partitioned environment. We model the motion of the robot in the environment as a Markov decision process (MDP) and translate the motion specification to(More)
— 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,(More)