Diagnosability Analysis of a Class of Hierarchical State Machines

This paper addresses the problem of fault detection and isolation for a particular class of discrete event dynamical systems called hierarchical finite state machines (HFSMs). A new version of the property of diagnosability for discrete event systems tailored to HFSMs is introduced. This notion, called L₁-diagnosability, captures the possibility of detecting an unobservable fault event using only high level observations of the behavior of an HFSM. Algorithms for testing L₁-diagnosability are presented. In addition, new methodologies are presented for studying the diagnosability properties of HFSMs that are not L₁-diagnosable. These methodologies avoid the complete expansion of an HFSM into its corresponding flat automaton by focusing the expansion on problematic indeterminate cycles only in the associated extended diagnoser.

The Structure of Visual Spaces

The “visual space” of an optical observer situated at a single, fixed viewpoint is necessarily very ambiguous. Although the structure of the “visual field” (the lateral dimensions, i.e., the “image”) is well defined, the “depth” dimension has to be inferred from the image on the basis of “monocular depth cues” such as occlusion, shading, etc. Such cues are in no way “given”, but are guesses on the basis of prior knowledge about the generic structure of the world and the laws of optics. Thus such a guess is like a hallucination that is used to tentatively interpret image structures as depth cues. The guesses are successful if they lead to a coherent interpretation. Such “controlled hallucination” (in psychological terminology) is similar to the “analysis by synthesis” of computer vision. Although highly ambiguous, visual spaces do have geometrical structure. The group of ambiguities left open by the cues (e.g., the well known bas-relief ambiguity in the case of shape from shading) may be interpreted as the group of congruences (proper motions) of the space. The general structure of visual spaces for different visual fields is explored in the paper. Applications include improved viewing systems for optical man-machine interfaces.     

A bacterial colony growth algorithm for mobile robot localization

Achieving robot autonomy is a fundamental objective in Mobile Robotics. However in order to realize this goal, a robot must be aware of its location within an environment. Therefore, the localization problem (i.e.,the problem of determining robot pose relative to a map of its environment) must be addressed. This paper proposes a new biology-inspired approach to this problem. It takes advantage of models of species reproduction to provide a suitable framework for maintaining the multi-hypothesis. In addition, various strategies to track robot pose are proposed and investigated through statistical comparisons. The Bacterial Colony Growth Algorithm (BCGA) provides two different levels of modeling: a background level that carries on the multi-hypothesis and a foreground level that identifies the best hypotheses according to an exchangeable strategy. Experiments, carried out on the robot ATRV-Jr manufactured by iRobot, show the effectiveness of the proposed BCGA.

High power GaN‐HEMT SPDT switches for microwave applications

In this article, the design, fabrication, and on‐wafer test of X‐Band and 2–18 GHz wideband high‐power SPDT MMIC switches in AlGaN/GaN technology are presented. The switches have demonstrated state‐of‐the‐art performance and RF fabrication yield better than 65%. Linear and power measurements for different control voltages have been reported and an explanation of the dependence of the power performances on the control voltage is given. In particular, the X‐band switch exhibits a 0.4 dB compression level at 10 GHz when driven by a 38 dBm input signal. The wideband switch shows a compression level of 1 dB at an input drive higher than 38 dBm across the entire bandwidth. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

System for measuring the coordinates of tire surfaces in transient conditions when rolling over obstacles: description of the system and performance analysis

This paper describes the development of a system for measuring surface coordinates (commonly known as "shape measurements") which is able to give the temporal evolution of the position of the tire sidewall in transient conditions (such as during braking, when there are potholes or when the road surface is uneven) which may or may not be reproducible. The system is based on the well-known technique of projecting and observing structured light using a digital camera with an optical axis which is slanted with respect to the axis of the projector. The transient nature of the phenomenon has led to the development of specific innovative solutions as regards image processing algorithms. This paper briefly describes the components which make up the measuring system and presents the results of the measurements carried out on the drum bench. It then analyses the performance of the measuring system and the sources of uncertainty which led to the development of the system for a specific dynamic application: impact with an obstacle (cleat test). The measuring system guaranteed a measurement uncertainty of 0.28 mm along the Z axis (the axial direction of the tire) with a measurement range of 250(X) x 80(Y) x 25(Z) mm(3), with the tire rolling at a speed of up to 30 km/h.     

A simple and accurate method for calibrating the oscillation amplitude of tuning-fork based AFM sensors

We have developed a simple and accurate method for calibrating the amplitude of vibration of quartz tuning fork sensors commonly used in atomic force- and near field optical-microscopy. Unlike interferometric methods, which require a complex optical setup, the method we present requires only a simple measurement of the electro-mechanical properties of the tuning-fork oscillator and can be performed in a matter of minutes without disturbing the experimental setup. Comparison with interferometric methods shows that an accuracy of better than few percent can be routinely achieved.     

Disturbance attenuation by dynamic output feedback for input-delay systems

This paper addresses the optimal disturbance attenuation problem by output feedback for multivariable linear systems with delayed inputs. The attenuation is optimal in the sense that the controller minimizes the maximal amplitude of the plant output in response to such a disturbance. The controller is a general feedback, involving an observer, a state predictor, and a predicted state feedback. The optimal disturbance attenuation problem is formulated in terms of an equivalent system without delay. The optimal bound of the disturbance attenuation is then characterized, and it is shown that the optimal controller tends to have high gains. A necessary and sufficient condition to guarantee the existence of an optimal solution is provided using the geometric approach.     

Building brains for bodies

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We are building an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to think by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.