… on two-dimensional (2D) trajectory planning, this paper proposes an improved deep
reinforcement learning (DRL) -based three-dimensional (3D) trajectory planning method for cellular …

… manipulation planning, the environment often changes due to unexpected obstacles rendering
previous demonstrations invalid. This paper presents a reinforcement learning algorithm …

… would also like to point out that our DQN-based trajectory planning approach is model-free
and does therefore not rely on any specific channel model. While a more accurate and …

… to directly obtain smooth trajectories. In this work we formulate the path planning problem
as a reinforcement learning problem and show that the trajectory planning model, generated …

… Abstract—In this work, we study the optimal trajectory of an … of reinforcement learning (RL)
with the UAV acting as an autonomous agent in the environment to learn the trajectory that …

… a learning-based robotic catheterization platform addressing those challenges, this approach
incorporates path integral reinforcement learning (… The robotic trajectories were optimized …

… Abstract—The trajectory planning … planning, which ignores the interactions between vehicle
participants. This paper proposes a hierarchical framework based on reinforcement learning …

… sets for safe trajectory planning [13]–[17]. In particular, we extend Reachability-based Trajectory
Design (RTD) [15], which uses a simplified, parameterized model to make plans. Offline, …

… planning structure based on reinforcement learning (RL) which is capable of performing
autonomous vehicle behavior planning … the behavior and trajectory planning system. We will …

… Aiming at trajectory planning for autonomous driving at dynamic highway … trajectory for
learning and trajectory planning, but set T to 30. It means that the first 3 seconds of the trajectories …