… trajectory planning. The primary contributions of this paper are summarized as follows: 1)
Considering the features of trajectory planning … of DRL methods in trajectory planning task. 2) …

… We adopt reinforcement learning for assisting UAVs to learn collision avoidance without
knowing the trajectories of other UAVs in advance. In addition, for each UAV, we use …

… Reinforcement Learning (HRL) framework for learning autonomous driving policies. We adapt
a state-ofthe-art algorithm, Hierarchical Double Deep Q-learning (h… waypoint trajectories to …

… 2) We show that the UAV’s trajectory planning problem in the clustered WSN can be
seen as a sequence of decisions. Hence, a sequence-to-sequence pointer networkA* (Ptr-A*) …

This article is concerned with the problem of planning optimal maneuver trajectories and
guiding the mobile robot toward target positions in uncertain environments for exploration …

… proposed, where several UAVs having different trajectories fly over the target area and …
reinforcement learning based trajectory control algorithm is proposed for managing the trajectory …

… -learning based navigation capabilities. Thus, we proposed to apply reinforcement learning
to space robot trajectory planning… the robot and the robot will learn how to complete the task. …

… two steps: trajectory planning and trajectory tracking. The trajectory planning generates one
… [18] proposed a time-dependent trajectory planning method. They used a quintic polynomial …

… trajectory planning algorithms to the safety of traffic flow, and subsequently, how should we
design CAV longitudinal trajectory planning … , the objective of trajectory planning is usually to …

… Another part of research focuses on different layers of Motion Planning, such as strategic
decisions, trajectory planning, and control. A wide range of techniques in Machine …