摘要
针对不确定环境中的飞行器多任务航迹规划问题展开研究,提出了一种基于飞行路线图的两阶段航迹规划框架,航迹规划分成学习和查询两个阶段,环境信息和飞行器约束条件分阶段体现。在该框架下,通过采用一种混合多任务动态航迹规划方法,分别在稀疏路线图上实时搜索初始航迹和在精细路线图上启发式搜索后备航迹,能够在具有预先未知威胁、可变飞行任务的战场环境中实时生成三维航迹。
Among the many open issues of development of unmanned air vehicles (UAVs), route planning is paid extensively attention. But the focus is concentrated on the route-planning problem in known environments. In this paper, the route-planning problem of UAVs in uncertain and mission-adaptable environments is addressed with the proposal of a two-phase route-planning framework. The route planning process is split into two phases: the learning phase and the query phase. Environmental information and mission constraints of UAVs are integrated into the building roadmap and searching for routes. A hybrid route planner is adopted based on roadmap, which queries the initial route for UAV on the sparse roadmap and searching for the spare route on the fine roadmap with the help of the initial route. This planner can give 3D route for UAV in a dynamic and multiple-mission environment in real-time.
出处
《航空学报》
EI
CAS
CSCD
北大核心
2004年第5期485-489,共5页
Acta Aeronautica et Astronautica Sinica
基金
海军工程大学科学研究基金(HGDJJ03030)
关键词
无人飞行器
航迹规划
随机路线图
动态威胁回避
实时处理
Aircraft landing
Learning systems
Online searching
Real time systems
Transportation routes
Unmanned vehicles
