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박성관(Sung Gwan Park),김동환(Dong Hwan Kim) 제어로봇시스템학회 2020 제어·로봇·시스템학회 논문지 Vol.26 No.11
In this study, the performance of autonomous flight was analyzed by introducing the PPO method as reinforcement learning for autonomous flight of drones. A simulator based on the dynamics of a drone was produced, and the performance of autonomous flight was confirmed when reinforcement learning was applied to a drone using this simulator. After that, the possibility of autonomous flight was confirmed by applying the PPO algorithm to the actual drone. Also, a lightweight embedded PC was attached to the drone to perform independent calculations to simultaneously construct obstacle avoidance and path planning.