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Dietrich, André; Zug, Sebastian; Kaiser, Jörg
Geometric Environment Modeling System (Inproceeding)
7th IFAC Conference on Manufacturing Modelling, Management and Control, pp. 1429–1434, International Federation of Automatic Control Saint Petersburg, Russia, 2013.
(Abstract | Links | BibTeX | Tags: Distributed Systems, Dual Reality, Environment Model, Instrumented Environment)
@inproceedings{dietrich2013gems,
title = {Geometric Environment Modeling System},
author = {André Dietrich and Sebastian Zug and Jörg Kaiser},
url = {http://eos.cs.ovgu.de/wp-content/uploads/2014/09/Geometric-Environment-Modelling-System.pdf},
year = {2013},
date = {2013-06-19},
booktitle = {7th IFAC Conference on Manufacturing Modelling, Management and Control},
pages = {1429–1434},
address = {Saint Petersburg, Russia},
organization = {International Federation of Automatic Control},
abstract = {Flexible system configurations and adaptability to changing environments and environmental conditions are key concerns for autonomous systems in future applications, either in industrial production processes, building automation, or health-care scenarios. New technologies for instrumented and smart environments support the distribution and acquisition of a diversity of information, but the organization, selection, validation, and interpretation according to certain contexts are still open issues. Therefore we propose a concept for separating environmental perception and modeling from the application logic. We apply a general model related to the idea of “mental models\’\’ used in cognitive science. It combines geometrical data with knowledge about sensors and actuators. This model is used to derive all information, which is required by an application, and to generate different environmental representations. We show that this approach is capable of solving different problems in the fields of distributed systems as well as instrumented environments and demonstrate its usability.},
keywords = {Distributed Systems, Dual Reality, Environment Model, Instrumented Environment}
}
Flexible system configurations and adaptability to changing environments and environmental conditions are key concerns for autonomous systems in future applications, either in industrial production processes, building automation, or health-care scenarios. New technologies for instrumented and smart environments support the distribution and acquisition of a diversity of information, but the organization, selection, validation, and interpretation according to certain contexts are still open issues. Therefore we propose a concept for separating environmental perception and modeling from the application logic. We apply a general model related to the idea of “mental models” used in cognitive science. It combines geometrical data with knowledge about sensors and actuators. This model is used to derive all information, which is required by an application, and to generate different environmental representations. We show that this approach is capable of solving different problems in the fields of distributed systems as well as instrumented environments and demonstrate its usability.
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