| Summary: | 碩士 === 國立中興大學 === 電機工程學系所 === 105 === Due to the rapid development of unmanned aerial vehicles (UAVs), they can be applied to many aspects, like rescue, sports, and entertainment. However, the autonomous control of UAVs is still a difficult problem to solve. Reinforcement learning (RL) method, which is a kind of unsupervised learning algorithm, is widely used in motion control and motion learning of robots. Such a learning algorithm can adapt itself to the model error even without building the model and can also gradually approximate to the real system through the learning process. Specifically, after taking an action according to the policy, the learning agent receives a numerical reward for every state transition from the environment and then learns from experiences to improve its performance such that it will achieve optimization eventually. In this thesis, the reinforcement learning method is applied to the control of a quadrotor. In particular, we exploit the PID control coefficients tuned by reinforcement learning to a quadrotor to maintain its stable flying gesture in unknown environments.
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