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Sensors Data Collection Scheme based UAV-Trajectory Optimization using Reinforcement Learning
Silvirianti,Soo Young Shin 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
In this paper, data collection of sensors is considered under trajectory optimization of unmanned aerial vehicle (UAV) utilize reinforcement learning. An optimized trajectory is learned to reach the goal point while collecting sensors data as much as possible using reinforcement learning under mentioned conditions. State-action-reward-state-action (SARSA) and Q-learning based UAV trajectory optimization algorithms are utilized to maximize the data collection during finite flight time. The simulation result shows that Q-learning outperformed SARSA and random movement strategy.