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Naslov:Hierarchical learning of robotic contact policies
Avtorji:ID Simonič, Mihael, Institut Jožef Stefan (Avtor)
ID Ude, Aleš, Institut Jožef Stefan (Avtor)
ID Nemec, Bojan, Institut Jožef Stefan (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://www.sciencedirect.com/science/article/pii/S0736584523001321
 
.pdf PDF - Predstavitvena datoteka, prenos (1,73 MB)
MD5: E411C83073559D4F47042661E627F1FD
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo IJS - Institut Jožef Stefan
Povzetek:The paper addresses the issue of learning tasks where a robot maintains permanent contact with the environment. We propose a new methodology based on a hierarchical learning scheme coupled with task representation through directed graphs. These graphs are constituted of nodes and branches that correspond to the states and robotic actions, respectively. The upper level of the hierarchy essentially operates as a decision-making algorithm. It leverages reinforcement learning (RL) techniques to facilitate optimal decision-making. The actions are generated by a constraint-space following (CSF) controller that autonomously identifies feasible directions for motion. The controller generates robot motion by adjusting its stiffness in the direction defined by the Frenet–Serret frame, which is aligned with the robot path. The proposed framework was experimentally verified through a series of challenging robotic tasks such as maze learning, door opening, learning to shift the manual car gear, and learning car license plate light assembly by disassembly.
Ključne besede:autonomous robot learning, learning, experience, compliance and impedance contro
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:12.09.2022
Datum sprejetja članka:08.09.2023
Datum objave:18.09.2023
Založnik:Elsevier
Leto izida:2023
Št. strani:[in press]
Številčenje:Vol. 86
Izvor:Nizozemska
PID:20.500.12556/DiRROS-17072 Novo okno
UDK:004
ISSN pri članku:1879-2537
DOI:doi.org/10.1016/j.rcim.2023.102657 Novo okno
COBISS.SI-ID:164894211 Novo okno
Avtorske pravice:© 2023 The Authors. Published by Elsevier Ltd.
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 19. 9. 2023;
Datum objave v DiRROS:21.09.2023
Število ogledov:404
Število prenosov:203
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Gradivo je del revije

Naslov:Robotics and computer-integrated manufacturing
Založnik:Elsevier
ISSN:1879-2537
COBISS.SI-ID:18810902 Novo okno

Licence

Licenca:CC BY-NC 4.0, Creative Commons Priznanje avtorstva-Nekomercialno 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc/4.0/deed.sl
Opis:Licenca Creative Commons, ki prepoveduje komercialno uporabo, vendar uporabniki ne rabijo upravljati materialnih avtorskih pravic na izpeljanih delih z enako licenco.
Začetek licenciranja:18.09.2023

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:strojno učenje, učenje, izkušnje


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