无人机航迹规划算法综述

A Review of UAV Trajectory Planning Algorithms

随着无人机技术的发展,飞行器自主飞行是无人机发展的主要趋势,无人机航迹规划问题日益受到重视。对航迹规划问题进行分类,将无人机航迹规划问题分为二维和三维环境进行深入分析。将现有航迹规划算法按照传统经典算法,如人工势场法和A^(*)算法等,和现代智能算法,如遗传算法、蚁群算法、粒子群算法等进行分类,并且详细介绍了各改进算法的优劣性和应用。归纳了目前新兴的航迹规划算法,分析了目前航迹规划所面临的问题。

With the development of UAV technology,the autonomous flight of the vehicle is the main trend of UAV development,and the UAV trajectory planning problem is now described.Firstly,the trajectory planning problem is classified,and the UAV trajectory planning problem is divided into two-dimensional and three-dimensional environments for in-depth analysis.Then,the existing track planning algorithms are classified according to traditional classical algorithms,such as artificial potential field method and A^(*) algorithm,and modern intelligent algorithms,such as genetic algorithm,ant colony algorithm,particle swarm algorithm,etc.,and each improved algorithm is introduced in detail.advantages and disadvantages and applications.Finally,the emerging trajectory planning algorithms are summarized,and the problems faced by the current trajectory planning are analyzed.