Investigating sim-to-real transfer for reinforcement learning-based robotic manipulation
In this project, model-free Deep Reinforcement Learning (DRL) algorithms were implemented to solve complex robotic environments. These include low- dimensional and high-dimensional robotic tasks. Low-dimensional tasks have state inputs that are discrete values such as robotic arm joint angles, posit...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/148803 |