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Generating symbolic representation from sensor data: Inferring knowledge in robotics competitions
Rodriguez Lera, Francisco Javier; Martín-Rico, F.; Matelián-Olivera, V.
2018In 2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)
Peer reviewed
 

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Keywords :
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
Disciplines :
Computer science
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.
External co-authors :
yes
Language :
English
Title :
Generating symbolic representation from sensor data: Inferring knowledge in robotics competitions
Publication date :
2018
Event name :
2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)
Event date :
25-4-2018 to 27-4-2018
Audience :
International
Main work title :
2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)
Peer reviewed :
Peer reviewed
Commentary :
261-266
Available on ORBilu :
since 13 November 2018

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