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

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.