摘要
根据雷达对无人机的瞬时探测概率模型以及无人机的运动特性,提出一种基于改进蚁群算法与Voronoi图相结合的无人机路径规划方法,使无人机突破雷达威胁环境的路径成本最低。将该方法与其他路径规划方法在所得路径燃油成本、威胁成本、总成本以及计算时间方面进行对比,表明该方法具有更低的路径成本和更少的计算时间。
According to the radar for unmanned aerial vehicle instantaneous detection probability model and motion characteristics of unmanned aerial vehicle, this paper presents an unmanned aerial vehicle path planning method based on improved Ant Colony Algorithm（ACA） and Voronoi diagram in order to minimize the path cost when unmanned aerial vehicle breaks through the threaten field with multiple radars. Compared with other three kinds of path planning methods in income fuel costs, threat path cost, total costs and computing time, this method has lower path cost and less computing time.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第4期206-209,共4页
Computer Engineering
基金
国家"863"计划基金资助项目"基于自主无人飞行器的田间作物遥感信息采集系统的研制与应用"(2006AA10Z204)
关键词
路径规划
蚁群算法
VORONOI图
无人机
path planning
Ant Colony Algorithm（ACA）
Voronoi diagram
unmanned aerial vehicle
