From Video Game to Real Robot: The Transfer between Action Spaces

Janne Karttunen, Anssi Kanervisto, Ville Kyrki, Ville Hautamaki

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

Abstrakti

Deep reinforcement learning has proven to be successful for learning tasks in simulated environments, but applying same techniques for robots in real-world domain is more challenging, as they require hours of training. To address this, transfer learning can be used to train the policy first in a simulated environment and then transfer it to physical agent. As the simulation never matches reality perfectly, the physics, visuals and action spaces by necessity differ between these environments to some degree. In this work, we study how general video games can be directly used instead of fine-tuned simulations for the sim-to-real transfer. Especially, we study how the agent can learn the new action space autonomously, when the game actions do not match the robot actions. Our results show that the different action space can be learned by re-training only part of neural network and we obtain above 90% mean success rate in simulation and robot experiments.

AlkuperäiskieliEnglanti
OtsikkoProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
KustantajaIEEE
Sivut3567-3571
Sivumäärä5
ISBN (elektroninen)9781509066315
DOI - pysyväislinkit
TilaJulkaistu - toukokuuta 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaIEEE International Conference on Acoustics, Speech and Signal Processing - Barcelona, Espanja
Kesto: 4 toukokuuta 20208 toukokuuta 2020
Konferenssinumero: 45

Julkaisusarja

NimiProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
KustantajaIEEE
ISSN (painettu)1520-6149
ISSN (elektroninen)2379-190X

Conference

ConferenceIEEE International Conference on Acoustics, Speech and Signal Processing
LyhennettäICASSP
MaaEspanja
KaupunkiBarcelona
Ajanjakso04/05/202008/05/2020

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