Intelligent robot manipulation with deep learning
The application of reinforcement learning (RL) in robotics has seen significant advancements across various sectors, yet a critical challenge persists: the simulation-to-reality (sim-to-real) gap. In real-world scenarios, robots frequently underperform due to their inability to access or accurate...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/176388 |