一种固定翼无人机快速避障算法

Zijie Lin, L. Castano, Huan Xu
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引用次数: 10

摘要

提出了一种用于固定翼无人机三维空间导航的快速避碰算法。该算法旨在通过快速避碰多种障碍物,提高飞机作战完成任务目标的能力。该算法将障碍物的几何避障和基于运动学的避障起始时间的选择结合起来,称为柔性几何避障算法。与当前的避撞航路点生成方法相比,FGA算法减少了90%的计算时间。避碰时间窗的起始点由碰撞可能性决定。利用该算法,无人驾驶飞行器能够在避碰成功后恢复其原始轨迹的同时,避开静态和动态障碍物。对不同任务场景的仿真表明,该方法在多障碍物避障方面比其他方法更有效。通过蒙特卡罗仿真和参数化结果验证了算法的有效性。此外,该算法对传感器数据类型没有特定要求,可以适用于合作和非合作入侵者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fast Obstacle Collision Avoidance Algorithm for Fixed Wing UAS
This paper presents a novel fast collision avoidance algorithm for navigation in 3D space of fixed-wing Unmanned Aerial Systems (UAS). This algorithm is aimed at increasing the ability of aircraft operations to complete mission goals by enabling fast collision avoidance of multiple obstacles. The new algorithm, named Flexible Geometric Algorithm (FGA), combines geometric avoidance of obstacles and selection of a critical avoidance start time based on kinematic considerations. FGA reduced computational time by 90% when compared to current waypoint generation methods for collision avoidance. The starting point for the avoidance time window is determined by collision likelihood. Using this algorithm, the (Unmanned Air Vehicle) UAV is able to avoid static and dynamic obstacles while still being able to recover its original trajectory after successful collision avoidance. Simulations for different mission scenarios show that this method is much more efficient at avoiding multiple obstacles than other methods. Algorithm effectiveness validation is provided with Monte Carlo simulations and parametric results. In addition, this algorithm does not have specific requirements on the sensor data types and can be applied to cooperative and non-cooperative intruders.
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