… In this work, a trajectory planning method based on a value-… The purpose of trajectory
planning is to reach the target … is used to generate the desired trajectory. Finally, the desired …

… ABSTRACTDeep reinforcement learning (DRL) has been … This paper proposes a DRL-based
trajectory planner for … A simulation study is conducted to investigate the trajectory planning …

… formulate a joint user association, UAV trajectory planning and power allocation problem
to … This paper exploits the centralized and the decentralized deep reinforcement learning (DRL…

… are evaluated for the considered UAV trajectory planning problem via the proposed QiRL
solution. For comparison, two CRL methods (ie, Qlearning with ϵ-greedy and Boltzmann …

… planning methods become inapplicable when a space robot is in motion. A trajectory-planning
strategy based on reinforcement learning … Time-optimal trajectory planning has been …

… This work studies online learning-based trajectory planning for … The AUV trajectories for
sampling are determined on an … The optimal trajectories of all the AUVs in the next epoch are …

… A flight trajectory planning optimization is formulated as a Partial Observable Markov …
onboard deep reinforcement learning algorithm to optimize the realtime trajectory planning of the …

… uses a reinforcement learning (RL) method to train a neural network controller as an integrated
aircraft navigation and guidance controller. It is used to optimize the flight trajectory and …

… decisions and make optimal flying trajectories represent fundamental research challenges.
In this … Thereafter, we propose a deep reinforcement learning (DRL) technique to jointly make …

… Behaviorbased methods learn cost functions that guide trajectory planning in compliance …
and trajectory planning using Deep Maximum Entropy Inverse Reinforcement Learning. To …