分层强化学习在无人机领域应用综述
A Review of the Application of Hierarchical Reinforcement Learning in the Field of Drones

分层强化学习是强化学习领域的一个重要分支。基于分而治之的思想，将一个复杂问题分解成多个子问题，最终解决整个问题。近年来，由于传感器能力的提高和人工智能算法的进步，基于分层强化学习的无人机自主导航成为研究热点。本篇文章对国内外发表的具有代表性的文章进行概述，首先分析无人机和分层强化学习的含义，其次重点研究了分层强化学习在无人机轨迹规划和资源分配的优化问题上的应用。
Hierarchical reinforcement learning is an important branch in the field of reinforcement learning. Based on the idea of divide and conquer, a complex problem is decomposed into multiple sub-problems and finally the entire problem is solved. In recent years, due to the improvement of sensor capabilities and the advancement of artificial intelligence algorithms, autonomous drone navigation based on hierarchical reinforcement learning has become a research hotspot. This article provides an overview of representative articles published at home and abroad. First, it analyzes the meaning of UAVs and hierarchical reinforcement learning. Secondly, it focuses on the application of hierarchical reinforcement learning in UAV trajectory planning and resource allocation problems.