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The problems of route and motion planning for an autonomous flight vehicle in uncertain environment

机译:不确定环境中自主飞行车辆的路线和运动规划问题

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Major route and motion planning problems for an autonomous flight vehicle (FV) in uncertain environment are considered. The first problem is planning a flight route between two given points with an obligatory mission of visiting all reference points from a given set. The route planning task is complicated by the presence of wind flows that affect the speed and trajectory of a flight vehicle. Time cost required to move between two points is suggested as a generalized optimization criterion. Quasi-optimal route planning algorithm is proposed that use the Hungarian method for the assignment problem as an auxiliary tool. The second problem is dynamic motion planning in the presence of obstacles in unknown environment. An algorithm for planning locally optimal routes for the purposeful low-altitude flight in the yaw plane is proposed. We assume that the map of the area is a priori not known and decisions are made only on the basis of information coming from the environment in real time. The last problem is controlling flight vehicle motion along the given route under wind loads. Simulating aircraft motion in an uncertain environment is performed with allowance for the constant and dynamic (random) components of wind flows. Simulation system is implemented in MATLAB Simulink program and contains mathematical models of a flight vehicle and wind loads, as well as a special intelligent control module for rapid response to changes in the external environment.
机译:考虑了不确定环境中自主飞行车辆(FV)的主要路线和运动规划问题。第一个问题是计划两个给定点之间的飞行路线,这是从给定集中访问所有参考点的强制性任务。通过影响飞行车辆的速度和轨迹的风流量,路线规划任务复杂。建议在两点之间移动所需的时间成本作为广义优化标准。建议使用匈牙利方法作为辅助工具的分配问题的准优化路线规划算法。第二个问题是在未知环境中存在障碍物的动态运动规划。提出了一种规划围绕偏航平面中的有目的的低空飞行局部最佳航线的算法。我们假设该地区的地图是先验的,并且仅基于实时来自环境的信息来进行决策。最后一个问题在于风负荷下的给定路线控制飞行车辆运动。模拟在不确定环境中的飞机运动是用风流量的恒定和动态(随机)组件的余量进行的。仿真系统在Matlab Simulink程序中实现,并包含飞行车辆和风力负载的数学模型,以及特殊的智能控制模块,可快速响应外部环境的变化。

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