… In addition, a reinforcement learning (RL) algorithm is presented in this work to optimize UAV
trajectories in response to the dynamic mobility of GUs for enhancing LoS connections. The …

… Some scenarios, eg deep RL trajectory planning for UAVs providing wireless connectivity
under battery power constraints, are related to CPP. An overview of UAV applications in …

… trajectories using proposed deep reinforcement learning algorithms. The DQN agent training
process requires careful balancing between exploration and exploitation. With a suitable …

… In recent years, deep Reinforcement Learning promises to automate the development of …
Combining deep reinforcement learning with trajectory planning at the toe level, reduces …

… In this paper, an improved approach to dynamic trajectory planning … trajectory with variable
sampling mechanism in the prediction domain for AGV. Subsequently, this auxiliary trajectory …

… Ayanian, and GS Sukhatme, “Downwashaware trajectory planning for large quadrotor
teams,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). …

… In this paper, a framework using reinforcement learning (RL) is proposed to … Qlearning
algorithm) grant the UAV the required artificial intelligence to autonomously find the trajectory and …

… Reinforcement Learning (IRL) [15] has been applied to learn a cost function from human
demonstration (teleoperation) [16], and a probability distribution over the set of joint trajectories …

… pattern, we propose an online AoI-based trajectory planning (A-TP) algorithm to adapt to
dynamic traffic generation patterns based on the reinforcement learning (RL) technique. …

… and prior works of trajectory planning using reinforcement learning didn’t consider the …
propose a trajectory planning method for autonomous vehicles using reinforcement learning. The …