An architecture for sim-to-real and real-to-sim experimentation in robotic systemsVrabič, Rok (Avtor) Škulj, Gašper (Avtor) Malus, Andreja (Avtor) Kozjek, Dominik (Avtor) Selak, Luka (Avtor) Bračun, Drago (Avtor) Podržaj, Primož (Avtor) roboticssimulationmachine learningreinforcement learningdigital twinResearch 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.20212022-01-31 14:13:41Članek v reviji134763UDK: 007.52ISSN pri članku: 2212-8271DOI: 10.1016/j.procir.2021.11.057COBISS_ID: 95688963OceCobissID: 95681795sl