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城市低空环境中多旋翼无人机在线航线规划方法
引用本文:吴宇,胡莘婷.城市低空环境中多旋翼无人机在线航线规划方法[J].控制与决策,2021,36(12):2851-2860.
作者姓名:吴宇  胡莘婷
作者单位:重庆大学航空航天学院,重庆400044;中国民航大学空中交通管理学院,天津300300
基金项目:重庆市自然科学基金项目(cstc2020jcyj-msxmX0602);中央高校基本科研业务费专项资金项目(2020 CDJ-LHZZ-066).
摘    要:为无人机规划一条从起点出发到达指定目标点的航线是实现无人机各种应用的重要前提.飞行过程中,无人机应具备对于各种动态变化快速响应并重新规划航线的能力.针对多旋翼无人机在飞行过程中可能遇到的各种动态变化,研究其在离散城市环境下的在线航线规划问题.首先,建立离散环境模型,并基于此模型定义无人机飞行规则;随后,建立无人机航线规划模型,包括对航点的约束条件及航线规划的指标;其次,将各种动态变化按照其对无人机的不同影响进行分类,分为固定禁飞区、合作无人机、非合作无人机3类,并针对不同种类动态变化特点,分别提出重新规划三维航线、改变飞行速度、滚动优化三维航线3种在线航线规划策略及综合应对策略;然后,改进快速随机扩展生成树算法(RRT),使其适合于离散城市环境.仿真实验中分别验证了所提出的在线航线规划策略在应对单一动态变化及组合动态变化时的有效性.

关 键 词:多旋翼无人机  城市环境  动态变化  在线航线规划  快速随机扩展生成树算法

An online route planning method for multi-rotor drone in urban environments
WU Yu,HU Xin-ting.An online route planning method for multi-rotor drone in urban environments[J].Control and Decision,2021,36(12):2851-2860.
Authors:WU Yu  HU Xin-ting
Affiliation:1. College of Aerospace Engineering,Chongqing University,Chongqing 400044,China;2. College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China
Abstract:A safe and efficient route from the start point to destination is a precondition for drone to realize its various applications. During the flight, the drone must be able to respond to various dynamic changes quickly and replan its route. For this purpose, the online route planning problem of multi-rotor drone is studied in the discrete urban environments in this paper. The model of discrete urban environments is established, based on which the flight rules of multi-rotor drone are defined. The route planning model is developed, and the constraints on path points and the index of evaluating the route planning are designed. According to the different influences of dynamic changes on multi-rotor drone''s flight, the dynamic changes are classified into three groups, i.e., fixed no-fly zone, cooperative drone and non-cooperative drone. Three strategies (replanning 3D route, changing flight velocity and roll optimization of 3D route) are proposed to cope with different types of dynamic changes. The proposed strategies are also valid when addressing the combined types of dynamic changes. The rapid-exploring random tree (RRT) algorithm is used to generate the route, and some modifications are carried out to make it suitable for the discrete urban environments. The validity of the proposed three online route planning strategies are verified in simulations, and it is also effective when the multi-rotor drone is facing more than one type of dynamic change. Simulation results demonstrate that the route generated online can avoid the bad effects brought by the dynamic changes.
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