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...
Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10234431/ |