Generating symbolic representation from sensor data: Inferring knowledge in robotics competitions

Reference : Generating symbolic representation from sensor data: Inferring knowledge in robotics ...


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/37251

Title :	Generating symbolic representation from sensor data: Inferring knowledge in robotics competitions
Language :	English
Author, co-author :	Rodriguez Lera, Francisco Javier [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)]
	Martín-Rico, F. [> >]
	Matelián-Olivera, V. [> >]
Publication date :	2018
Main document title :	2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)
Peer reviewed :	Yes
Audience :	International
Event name :	2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)
Event date :	25-4-2018 to 27-4-2018
Keywords :	[en] inference mechanisms;knowledge representation;mobile robots;navigation;sensors;recurrent problem;artificial systems;sub-symbolic layer;robotics competitions;sensor data transformation;knowledge inference;home competition;European robotics league;navigation task;symbolic knowledge representation;Robot sensing systems;Databases;Planning;Computer architecture;Autonomous robots;Task analysis;grounding;representation;octomap;ROS
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/37251
DOI :	10.1109/ICARSC.2018.8374193
Commentary :	261-266

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