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Titel:

A Robust Stability Approach to Robot Reinforcement Learning based on a Parameterization of Stabilizing Controllers

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Friedrich, Stefan R.; Buss, Martin
Abstract:
Reinforcement learning has become more and more popular in robotics for acquiring feedback controllers. Many approaches aim for learning a controller from scratch, i.e., data-driven without any modeling of the physical plant. However, stability properties of the closed loop are often not considered, or established only a-posteriori or ad hoc. We propose to employ reinforcement learning in the context of model-based control, allowing to learn in a framework of stabilizing controllers built...     »
Stichworte:
Adaptation models; Adaptive control; Learning (artificial intelligence); Robotcontrol; Stability analysis
Kongress- / Buchtitel:
2017 IEEE International Conference on Robotics and Automation (ICRA)
Ausrichter der Konferenz:
IEEE
Datum der Konferenz:
May 29 - June 3, 2017
Jahr:
2017
Monat:
May
Seiten:
3365-3372
Sprache:
en
Volltext / DOI:
doi:10.1109/ICRA.2017.7989382
Semester:
SS 17
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