Authors:
Gilles Neyens
and
Denis Zampunieris
Affiliation:
Department of Computer Science, University of Luxembourg and Luxembourg
Keyword(s):
Decision Support System, System Software, Proactive Systems, Robotics.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge-Based Systems
;
Pattern Recognition
;
Robotics
;
Software Engineering
;
Symbolic Systems
Abstract:
Robots have to be able to function in a multitude of different situations and environments. To help them achieve this, they are usually equipped with a large set of sensors whose data will be used in order to make decisions. However, the sensors can malfunction, be influenced by noise or simply be imprecise. Existing sensor fusion techniques can be used in order to overcome some of these problems, but we believe that data can be improved further by computing context information and using a proactive rule-based system to detect potentially conflicting data coming from different sensors. In this paper we will present the architecture and scenarios for a generic model taking context into account.