<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://repozitorij.uni-lj.si/IzpisGradiva.php?id=134763"><dc:title>An architecture for sim-to-real and real-to-sim experimentation in robotic systems</dc:title><dc:creator>Vrabič,	Rok	(Avtor)
	</dc:creator><dc:creator>Škulj,	Gašper	(Avtor)
	</dc:creator><dc:creator>Malus,	Andreja	(Avtor)
	</dc:creator><dc:creator>Kozjek,	Dominik	(Avtor)
	</dc:creator><dc:creator>Selak,	Luka	(Avtor)
	</dc:creator><dc:creator>Bračun,	Drago	(Avtor)
	</dc:creator><dc:creator>Podržaj,	Primož	(Avtor)
	</dc:creator><dc:subject>robotics</dc:subject><dc:subject>simulation</dc:subject><dc:subject>machine learning</dc:subject><dc:subject>reinforcement learning</dc:subject><dc:subject>digital twin</dc:subject><dc:description>Research in the area of robotic systems has greatly benefited from the use of simulation models. Recent approaches allow the transfer of developed algorithms from simulation to reality (sim-to-real) and increasingly accurate representations of real systems as simulation models (real-to-sim). The paper presents an architecture based on open software that supports simultaneous experiments on real robots and their simulation models. Two illustrative examples are shown: a digital twin of an industrial robot and a sim-to-real transfer in an autonomous mobile robot system. The possibilities of future research on the interaction between robotic systems and their simulation models are discussed.</dc:description><dc:date>2021</dc:date><dc:date>2022-01-31 14:13:41</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>134763</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
