Optimizing Reinforcement Learning Control Model in Furuta Pendulum and Transferring it to Real-World

Reinforcement learning does not require explicit robot modeling as it learns on its own based on data, but it has temporal and spatial constraints when transferred to real-world environments. In this research, we trained a balancing Furuta pendulum problem, which is difficult to model, in a virtual...

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Bibliographic Details
Main Authors: Myung Rae Hong, Sanghun Kang, Jingoo Lee, Sungchul Seo, Seungyong Han, Je-Sung Koh, Daeshik Kang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10234431/