摘要
为简化无人机飞行路径规划算法并提高其避障效果,本文提出一种人工势场法和A星算法相结合的路径规划算法:以人工势场法指导全局路径规划,通过引力场控制无人机的飞行方向;以A星算法指导局部路径规划,避让大型障碍物.仿真试验证明,该算法与人工势场法和A星算法相比,提高了避障效果,缩短了搜索时间.
In order to improve the avoidance effect and simplify the scanning process of the flight path planning algorithm of the unmanned aerial vehicle,an improved algorithm combining the artificial potential field method and the A-Star algorithm is proposed in this paper.The global path planning is guided by the artificial potential field method.In this method,the flying direction of the unmanned aerial vehicle is controlled by the gravitational field.And the local path planning is guided by the A-Star algorithm to avoid the large obstacles.The simulation test proves that this algorithm has better evasive effect and shorter search time compared with the artificial potential field method and the A-Star algorithm.
作者
王云常
戴朱祥
李涛
WANG Yunchang;DAI Zhuxiang;LI Tao(College of automation,Nanjing University of Information Science&Technology,Nanjing 210044,China)
出处
《扬州大学学报（自然科学版）》
CAS
北大核心
2019年第3期36-38,49,共4页
Journal of Yangzhou University：Natural Science Edition
基金
国家自然科学基金资助项目(61573189)
江苏省人力资源和社会保障厅“六大人才高峰”资助项目(2015-DZXX-013)
关键词
无人机
路径规划
人工势场法
A星算法
避障
unmanned aerial vehicle(UAV)
path planning
artificial potential field method
A-Star algorithm
avoid obstacles
作者简介
联系人:李涛,E-mail:litaojia@163.com.
