[en] Robots traditionally have a wide array of sensors that allow them to react to the environment and make appropriate decisions. These sensors can give incorrect or imprecise data due to malfunctioning or noise. Sensor fusion methods try to overcome some of these issues by using the data coming from different sensors and combining it. However, they often don’t take sensor malfunctioning and a priori knowledge about the sensors and the environment into account, which can produce conflicting information for the robot to work with. In this paper, we present an architecture and process in order to overcome some of these limitations based on a proactive rule-based system.
Disciplines :
Computer science
Author, co-author :
NEYENS, Gilles ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
ZAMPUNIERIS, Denis ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
no
Language :
English
Title :
Proactive Middleware for Fault Detection and Advanced Conflict Handling in Sensor Fusion
Publication date :
2019
Event name :
18th International Conference, Artificial Intelligence and Soft Computing (ICAISC) 2019 Zakopane, Poland, June 16–20, 2019
Event organizer :
IEEE Poland Section Computational Intelligence Society Chapter
Event place :
Zakopane, Poland
Event date :
16 – 20 June, 2019
Audience :
International
Main work title :
Proceedings of the 18th International Conference, ICAISC 2019 Zakopane, Poland, June 16–20, 2019, Part I & II
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