Implementation of the swarm intelligence behavior social foraging in unmanned aerial vehicle (UAV) quadrotors

• Main Author: Faelden, Gerard Ely U.
• Format: text
• Language: English
• Published: Animo Repository 2016
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/5183
• Institution: De La Salle University

The growing interest in quadrotor research led to the creation of control algorithms for multiple quadrotor groups. One of the novel approaches in multiple quadrotor control is swarm robotics. It aims to mimic social behaviors of animals and insects. This paper presents the physical implementation of the swarm behavior social foraging in unmanned aerial vehicle quadrotors. To achieve this, it first explores the basic behavior of aggregation. It is implemented over a quadrotor swarm testbed that makes use of external motion capture cameras. The completed algorithm makes use of the artificial potential function model combined with the environment resource profile model. Results show successful demonstration of the social foraging algorithm with minimal error in position. It is tested for an increasing number of quadrotors and errors are seen to increase with swarm size. Results show an error of 3.293 cm in target position for aggregation while showing an increase in aggregation speed and time in aggregate as the number of swarm members increases. The static environment social foraging test shows an error of 5.667 cm from the target position while the dynamic environment test posted an error of 8.395 cm an increase brought about the changing environment. All the tests show successful demonstration of the swarming behavior which can now mark the start of development of applications such as precision agriculture, search and rescue and unknown area exploration.