Reference : Proactive Middleware for Fault Detection and Advanced Conflict Handling in Sensor Fusion

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/39711

Title :	Proactive Middleware for Fault Detection and Advanced Conflict Handling in Sensor Fusion
Language :	English
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) >]
Publication date :	2019
Main document title :	Proceedings of the 18th International Conference, ICAISC 2019 Zakopane, Poland, June 16–20, 2019, Part I & II
Publisher :	Springer
Collection and collection volume :	Part II
Pages :	643-653
Peer reviewed :	Yes
On invitation :	No
Audience :	International
ISBN :	978-3-030-20915-5
Event name :	18th International Conference, Artificial Intelligence and Soft Computing (ICAISC) 2019 Zakopane, Poland, June 16–20, 2019
Event date :	16 – 20 June, 2019
Event organizer :	IEEE Poland Section Computational Intelligence Society Chapter
Event place (city) :	Zakopane
Event country :	Poland
Keywords :	[en] Rule-based systems ; Sensor fusion ; Conflict handling ; Proactive computing
Abstract :	[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.
Permalink :	http://hdl.handle.net/10993/39711
DOI :	10.1007/978-3-030-20915-5_57
Other URL :	https://doi.org/10.1007/978-3-030-20915-5_57
Mentions required by the publisher for OA :	© Springer Nature Switzerland AG 2019
Commentary :	© Springer Nature Switzerland AG 2019

	File(s) associated to this reference
	Fulltext file(s): File Commentary Version Size Access Open access ICAISC_6472.pdf Author postprint 428.88 kB View/Open Additional material(s): File Commentary Size Access Open access IcaiscPosterPrintA1.pdf Poster 1.47 MB View/Open

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