Jul 21, 2023 · Therefore, this paper proposes a new deep reinforcement learning algorithm, namely Multiple Pools Twin Delay Deep Deterministic Policy Gradient (MPTD3) ...

Mar 30, 2024 · Full Length Article. Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments.

Mar 29, 2024 · Concerning the end-to-end autonomous UAV obstacle avoidance problem, a deep reinforcement learning-based autonomous flight obstacle avoidance method, called.

Sep 15, 2023 · This framework enables multi-UAV to autonomously learn real-time target tracking and obstacle avoidance. ... A. Deep reinforcement learning for UAV target ...

Jan 8, 2024 · This paper formulates it as a deep reinforcement learning problem, in which the RL Agent extracts preprocessed environmental information and sensor information ...

Oct 23, 2023 · An end-to-end approach to autonomous navigation that is based on deep reinforcement learning (DRL) with a survival penalty function is proposed in this ...

Dec 28, 2023 · The tracking of targets by UAVs in different environments is realized. (Bae et al. 2023) use curriculum learning to model within visual range air combat.

Jan 12, 2024 · Complex flight environments put forward higher demands for path planning algorithms of UAVs, thus the research in autonomous obstacle avoidance path planning ...

Dec 23, 2023 · To address this issue, this paper proposes a vision-based plan- ning system that combines tracking and trajectory predic- tion of dynamic obstacles to achieve ...

Feb 9, 2024 · This study conducts research on the path planning problem for UAVs by introducing deep reinforcement learning algorithms to achieve autonomous path planning in ...