A genetic algorithm approach to swarm centroid tracking in quadrotor unmanned aerial vehicles

2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2014-11-01 DOI:10.1109/HNICEM.2014.7016217

R. Nakano, A. Bandala, G. E. Faelden, Jose Martin Z. Maningo, E. Dadios

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引用次数: 11

Abstract

One of the trademark behaviors of a swarm is aggregation. Aggregation is the ability to gather swarm members around a specific point in space. The goal is to keep an object, stationary or moving, at the center of the swarm. This paper presents a novel approach to centroid tracking in robotic swarms. Genetic algorithm is used in quadrotor unmanned aerial vehicles to keep the object being tracked at the center while minimizing two parameters: the distance travelled by each quadrotor and the distance of each quadrotor from the object. Centroid tracking was found to have an average error of 0.0623568 units for swarm populations ranging from 10 to 100 with the lower swarm populations exhibiting lower errors. Convergence did not exceed the maximum of 23 milliseconds for populations less than 30. These results show that the algorithm is well-suited for implementation in swarms with lower numbers of quadrotors.

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基于遗传算法的四旋翼无人机群质心跟踪

群体的一个标志性行为是聚集。聚集是指将群体成员聚集在空间中特定点周围的能力。目标是保持一个物体，静止或移动，在群体的中心。提出了一种新的机器人群质心跟踪方法。在四旋翼无人机中，采用遗传算法使目标保持在中心位置，同时使每个四旋翼的飞行距离和每个四旋翼与目标的距离最小化。在10 ~ 100个群体中，质心跟踪的平均误差为0.0623568个单位，较小的群体群体误差较小。对于小于30的种群，收敛不超过最大23毫秒。这些结果表明，该算法非常适合在较少数量的四旋翼机群中实现。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

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