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End-to-End Autonomous Quadcopter using Reinforcement Learning
This thesis investigates the potential of Reinforcement Learning (RL) for achieving robust and adaptable quadcopter control, focusing on trajectory and attitude stabilization. We compare state-of-the-art RL algorithms, specifically Proximal Policy Optimization (PPO), against traditional Proportional...
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| Format: | Thesis |
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AUC Knowledge Fountain
2024
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