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Optimal Online Path Planning with Multi-Obstacles Avoidance for Autonomous Fixed-Wing Unmanned Aerial Vehicles.

机译:自主固定翼无人飞行器具有多障碍避免的最优在线路径规划。

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摘要

Fixed-Wing Unmanned Aerial Vehicles (UAVs) are popular in military, commercial and civilian fields featuring its higher flight speed and lower consumption of energy compared with quadrotors. Apart from the speed feature, flexibility and intelligence play important roles as well. In order to obtain a safe and short flight path for a given task, an intelligent flight path planning algorithm is required. In this paper, a fast optimal flight path planning algorithm for fixed-wing UAVs, based on a refined Dubins Path geometry, is proposed. To ensure the safety feature, this algorithm consists the ability of collision avoidance for known obstacles in a limited sight, with given safe radius or curvature. The avoidance ability is guaranteed by a fast collision points generation method, which allows the UAVs to avoid collisions by flying a Dubins Path with the given safe radius or curvature. The input contains longitude, latitude, heading angles, turning radius and rotation direction. Among the input, the rotation direction is a binary/integer variable. The nonlinear constraints are implemented to evaluate the Euclidean distance violation between path and obstacles. Thus, a single objective, mixed-binary, nonlinear optimization problem is posed so as to find out a short and safe flight path among a plenty of possibilities.
机译:固定翼无人飞行器(UAV)在军事,商业和民用领域非常流行,与四旋翼飞行器相比,它具有更高的飞行速度和更低的能耗。除了速度功能外,灵活性和智能性也起着重要作用。为了获得用于给定任务的安全且短的飞行路径,需要智能的飞行路径计划算法。本文提出了一种基于改进的Dubins路径几何的固定翼无人机快速最优飞行路径规划算法。为了确保安全性,该算法包括在给定安全半径或曲率的情况下,在有限的视野内避免已知障碍物碰撞的能力。通过快速的碰撞点生成方法可以确保避让能力,该方法使无人机可以通过以给定的安全半径或曲率飞行杜宾斯路径来避免碰撞。输入包含经度,纬度,航向角,转弯半径和旋转方向。在输入中,旋转方向是二进制/整数变量。实施非线性约束以评估路径与障碍物之间的欧几里得距离违规。因此,提出了一个单目标,混合二进制,非线性优化问题,以便在众多可能性中找到一条短而安全的飞行路径。

著录项

  • 作者

    Guo, Chenrui.;

  • 作者单位

    State University of New York at Buffalo.;

  • 授予单位 State University of New York at Buffalo.;
  • 学科 Mechanical engineering.;Aerospace engineering.
  • 学位 M.S.
  • 年度 2017
  • 页码 154 p.
  • 总页数 154
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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