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Pattern Forming Acceleration for Dancing UAVs Using Ant Colony Optimization

机译:基于蚁群算法的无人机飞行模式形成加速

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A dancing UAVshow is a performance where a number of UAVs fly and form certain patterns. The dancing UAV performance is very limited by the show time and also the flying time of each UAV. Beside the time problem, determining the trajectory of each UAV to form certain patterns in a three-dimensional area is a problem. To overcome the time problem and determine the trajectory, it is necessary to determine the best waypoint and trajectory. In this paper, we use Ant Colony Optimization (ACO) as a method to figure out the best waypoint and trajectory. Experiments using simulations were carried out to see the magnitude of the effect of selecting the best waypoint and trajectory using the ACO. The results of the experiment show that method can shorten the distance, especially for the pattern that formed with the large number of UAVs.
机译:跳舞的无人机表演是许多无人机飞行并形成某些模式的表演。舞蹈无人机的性能受表演时间以及每个无人机飞行时间的限制。除了时间问题之外,确定每个无人机的轨迹以在三维区域中形成某些模式也是一个问题。为了克服时间问题并确定轨迹,必须确定最佳航路点和轨迹。在本文中,我们使用蚁群优化(ACO)作为找出最佳航路点和轨迹的方法。进行了使用模拟的实验,以了解使用ACO选择最佳航路点和轨迹的效果的大小。实验结果表明,该方法可以缩短距离,特别是对于由大量无人机形成的模式而言。

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