Title :
Formation stabilization algorithm for swarm tracking in unmanned aerial vehicle (UAV) quadrotors
Author :
Bandala, Argel A. ; Vicerra, Ryan Rhay P. ; Dadios, Elmer P.
Abstract :
This paper presents swarm formation algorithm for swarm tracking behavior in multi robotic system of flying quadrotor unmanned aerial vehicles (QUAV). Multi robotic system ensures the success of the task through the increase in members of the swarm. This characteristic is very suitable for tracking moving objects. Another key feature would be the decentralized processing of the swarm. The loss of a swarm member would not contribute significantly to the swarm. The behaviors were patterned to biological traits of insects and animals and are applied to computer applications. Simulations were performed and results showed that swarm tracking accuracy yielded 89.23%. This result is due to the accuracy of 84.65% of the formation behavior of the swarm. Furthermore, the aggregation behavior further contributed with an accuracy of 90.62%.
Keywords :
autonomous aerial vehicles; decentralised control; helicopters; multi-robot systems; position control; stability; UAV quadrotor; aggregation behavior; decentralized processing; flying quadrotor unmanned aerial vehicles; formation behavior; formation stabilization algorithm; moving object tracking; multirobotic system; swarm formation algorithm; swarm tracking behavior; unmanned aerial vehicle quadrotor; Accuracy; Animals; Robot kinematics; Target tracking; Unmanned aerial vehicles; Social Behaviors; Swarm Intelligence; Swarm Tracking. (key words); Swarm robotics; Unmanned Aerial Vehicle;
Conference_Titel :
TENCON 2014 - 2014 IEEE Region 10 Conference
Conference_Location :
Bangkok
Print_ISBN :
978-1-4799-4076-9
DOI :
10.1109/TENCON.2014.7022455