To enable the robots to adapt to a more diverse distribution of obstacles, we introduce DRAL, a novel deep reinforcement learning method that leverages adaptive control during the unknown …

Employing a deep learning approach, a deep reinforcement adaptive learning algorithm is trained to develop control strategy that emulates the decision-making process of an expert pilot. We …

2024年9月5日 · Integrating our DRAL algorithm enables multiple UAVs to learn optimal control strategies that adapt to dynamic conditions and uncertainties. This innovation enhances the …

2024年4月5日 · This article presents a literature review of the past five years of studies using Deep Reinforcement Learning (DRL) and Inverse Reinforcement Learning (IRL) in robotic …

2024年9月5日 · Integrating our DRAL algorithm enables multiple UAVs to learn optimal control strategies that adapt to dynamic conditions and uncertainties. This innovation enhances the …

2024年10月9日 · Kangtong Mo, Linyue Chu, Xingyu Zhang, Xiran Su, Yang Qian, Yining Ou, Wian Pretorius: DRAL: Deep Reinforcement Adaptive Learning for Multi-UAVs Navigation in …

2022年3月21日 · 本文主要介绍模仿学习中的两种主流方法，逆强化学习（IRL）和生成对抗模仿学习（GAIL）_gail.

集成我们的 DRAL 算法使多个无人机能够学习适应动态条件和不确定性的最佳控制策略。 这项创新增强了室内导航的稳健性和灵活性，并为有限空间内复杂的多无人机操作开辟了新的可能性。

The paper introduces a novel deep reinforcement learning-based approach called DRAL to help guide multiple drones (UAVs) as they navigate through unknown indoor spaces.

1983年8月25日 · Ultraviolet irradiation of the DNA substrate at relatively low doses inhibits the activity of Dral by “protecting” the recognition sequence and this may be exploited to give …