Publication Details

SELECT * FROM publications WHERE Record_Number=11287
Reference TypeThesis
Author(s)Menzenbach, R.
Year2019
TitleBenchmarking Sim-2-RealAlgorithms on Real-WorldPlatforms
Journal/Conference/Book TitleBachelor Thesis
KeywordsSim-to-real, Domain Randomization, Benchmarking
AbstractLearning from simulation is particularly useful, because it is typically cheaper and safer than learning on real-worldsystems. Nevertheless, the transfer of learned behavior from the simulation to the real word can impose difficultiesbecause of the so-called ’reality gap’. There are multiple approaches trying to close the gap. Although many benchmarksof reinforcement learning algorithms exist, state-of-the-art sim-2-real methods are rarely compared. In this thesis, wecompare two recent methods on Furuta pendulum swing up and ball balancing tasks. The performed benchmarks aimat assessing sim-2-sim and sim-2-real transferability. We show that the application of sim-2-real methods significantlyimproves the transferability of learned behavior.
Date01.10.2019
Link to PDFhttps://www.ias.informatik.tu-darmstadt.de/uploads/Team/FabioMuratore/Menzenbach--BenchmarkingSim2RealAlgorithmsOnRealWorldPlatforms.pdf

  

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