[1]樊娇,雷涛,韩伟,等.无人机航迹规划技术研究综述[J].郑州大学学报(工学版),2021,42(03):39.
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无人机航迹规划技术研究综述()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
42
期数:
2021年03期
页码:
39
栏目:
出版日期:
2021-05-10

文章信息/Info

作者:
樊娇 雷涛 韩伟 王锐
文献标志码:
A
摘要:
航迹规划是无人机自主飞行的关键技术之一典型的航迹规划分为3个步骤:首先充分考虑各种威胁环境,进行飞行航迹的初步规划,其次利用优化搜索算法找出最佳航迹,最后进行航迹平滑处理系统梳理了近些年关于无人机航迹规划的研究现状,分析了航迹规划过程中动力学约束和环境约束等因素阐述了航迹规划涉及的关键技术,包括地形获取¸威胁及代价建模¸航迹规划算法以及航迹平滑处理等,并进一步对常用的航迹规划算法,如A*算法¸遗传算法¸蚁群算法¸粒子群算法,以及常用的航迹平滑算法B样条曲线法进行了分析和归纳总结了当前无人机航迹规划模型构建与航迹规划算法两个方面存在的问题最后对无人机航迹规划未来可能的发展趋势进行了展望,指出构建合理的航迹规划的体系¸先进的在线航迹规划算法研究,以及多无人机协同航迹规划是未来的研究趋势。
Abstract:
Path planning is one of the key technologies of UAV autonomous flight. The typical path planning can be divided into three steps:firstly , the preliminary planning of flight path should be carried out by fully considering various threat environments secondly , the optimal path should be found by using the optimization search algorithm finally, the path should be smoothed.This paper systematically summarizes the studies of UAV path planning in recent yearsanalyzes the flight airspace,dynamic constraints and environmental constraints in the process of path planningexpounds the key technologies involved in path planning,including terrain acquisition,threat and cost modeling,path planning algorithm and path smoothing and further analyzes and summarizes the common path planning algorithms,such as A*search algorithm,genetic algorithm , ant colony algorithm,particle swarm optimization algorithm, and the common path smoothing algorithm B-spline curve method and summarizes the problems of the current UAV path planning model construction and path planning search algorithm.Finally ,some potential future development trends of UAN path planning are proposed , including the construction of reasonable path planning system , the study of advanced online path planning algorithm ,and the cooperative path planning of multi-UAV.
更新日期/Last Update: 2021-06-24