La rencontre de l’intelligence ambiante et de la robotique d’assistance a donné naissance à ce que nous avons appelé robotique ambiante d’assistance car destinée à assister une personne en perte d’autonomie. Elle s’appuie sur l’existence de réseaux d’objets communicants présents dans l’environnement de la personne pour décliner un ensemble de services et de téléservices destinés à faciliter la vie quotidienne de cette personne et de son entourage. Un, voir plusieurs robots peuvent être présents dans cet environnement. Une communauté scientifique récente s’est construite autour de la robotique ubiquitaire. Tandis que les robots des générations précédentes ont été conçus pour réaliser des tâches spécifiques et construits en tant qu’unité indépendante, la nouvelle génération vise l’ubiquité. L’autonomie du robot est obtenue par une interaction étroite entre le robot et l’environnement ambiant communicant. Dans le contexte de l’intelligence ambiante, les objets communicants de l’environnement peuvent jouer un rôle "facilitateur" en aidant le robot à se localiser, naviguer, rechercher un objet. Inversement, le robot peut être vu comme un objet communicant qui est mis à contribution par des services autres que l’assistance à la personne en perte d’autonomie. Ainsi le premier objectif de cette thèse est de proposer une architecture informatique permettant la coopération entre le robot et les objets communicants présents dans l’environnement tels que les capteurs ou les actionneurs. Le deuxième objectif est de proposer une méthode de localisation par coopération robot-environnement communicant. Notre ambition est de localiser avec certitude le robot dans une zone de l’habitat. / The meeting of ambient intelligence and assistive robotics gave birth to ambient assistive robotics which aims at assisting a person in loss of autonomy. It relies on the existence network of communicating objects present in the environment of the person. The objective is to propose a set of services and teleservices for facilitating the person's daily life. One or more robots can be present in this environment. Previous generation of robots have been designed to perform tasks specific and built as an independent unit, while the new generation of robots tries to take advantage of ubiquity. In this framework, the robot autonomy is obtained by a close interaction between the robot and the ambient environment. Up to recent years the robot moved in a rather hostile environment which did not facilitate its task. In the context of ambient intelligence, the communicating objects of ambient environment can play a "facilitator" role in helping the assistive robot for locating itself, searching for a person … Conversely, the robot can be seen as a communicating object which is used by services to the person in loss of autonomy. The first objective of this thesis is to propose an architecture for cooperation between the robot and communicating objects and the second objective is to propose a localization method by cooperation of ambient environment and a mobile robot.

Currently available wind-wave prediction models require a prohibitive amount of computing time for simulating non-linear wave-wave interactions. Moreover, some parts of wind-wave generation processes are not fully understood yet. For this reason accurate predictions are not always guaranteed. In contrast, Artificial Neural Network (ANN) techniques are designed to recognize the patterns between input and output so that they can save considerable computing time so that real-time wind-wave forecast can be available to the navy and commercial ships. For this reason, this study tries to use ANN techniques to predict waves for winter storms and hurricanes with much less computing time at the five National Oceanic and Atmospheric Administration (NOAA) wave stations along the East Coast of the U.S. from Florida to Maine (station 44007, 44013, 44025, 44009, and 41009). In order to identify prediction error sources of an ANN model, the 100% known wind-wave events simulated from the SMB model were used. The ANN predicted even untrained wind-wave events accurately, and this implied that it could be used for winter-storm and hurricane wave predictions. For the prediction of winter-storm waves, 1999 and 2001 winter-storm events with 403 data points had 1998 winter-storm events with 78 points were prepared for training and validation data sets, respectively. In general, because winter-storms are relatively evenly distributed over a large area and move slowly, wind information (u and v wind components) over a large domain was considered as ANN inputs. When using a 24-hour time-delay to simulate the time required for waves to be fully developed seas, the ANN predicted wave heights (r = 0.88) accurately, but the prediction accuracy of zero-crossing wave periods was much less (r = 0.61). For the prediction of hurricane waves, 15 hurricanes from 1995 to 2001 and Hurricane Bertha in 1998 were prepared for training and validation data sets, respectively. Because hurricanes affect a relatively small domain, move quickly, and change dramatically with time, the location of hurricane centers, the maximum wind speed, central pressure of hurricane centers, longitudinal and latitudinal distance between wave stations and hurricane centers were used as inputs. The ANN predicted wave height accurately when a 24-hour time-delay was used (r = 0.82), but the prediction accuracy of peak-wave periods was much less (r = 0.50). This is because the physical processes of wave periods are more complicated than those of wave heights. This study shows a possibility of an ANN technique as the winter-storm and hurricane-wave prediction model. If more winter-storm and hurricane data can be available, and the prediction of hurricane tracks is possible, we can forecast real-time wind-waves more accurately with less computing time.

This dissertation addresses the problem of developing intelligent computer integrated manufacturing (ICIM) systems. The research objectives are to provide an object-oriented development methodology for ICIM systems supported with tools and techniques to elicit and specify domain knowledge and information. Currently, no suitable methodologies or modeling techniques exist for realizing ICIM systems. Existing methodologies represent portions of ICIM but lack the richness necessary to conceptualize and implement ICIM systems. / Research contributions include composition of an object-oriented detailed methodology with phases and phase dependencies for requirements analysis and design of ICIM systems and the development of a model, ROADMAP, used for knowledge elicitation and specification of the manufacturing domain. Additional contributions include supporting techniques for control knowledge elicitation, techniques for object specification, and expansion of standard evaluation techniques for design of object-oriented systems. / Source: Dissertation Abstracts International, Volume: 52-06, Section: B, page: 3157. / Major Professor: Abraham Kandel. / Thesis (Ph.D.)--The Florida State University, 1991.

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