Assessment of Distributed Flocking Algorithms for Multi-Fixed-Wings UAVs using SIL Simulation

Abstract

This paper aims to implement and validate the flocking approaches known as Olfati-Saber and Vásárhelyi algorithms that are originally developed for fully-actuated systems for coordinating underactuated Unmanned Aerial Vehicles (UAVs) teams in a stochastic environment using a Software-in-the-Loop (SIL) Simulation Platform based on realistic aircrafts with nonlinear dynamic models. These algorithms allow the UAVs to maintain the cohesion, alignment and separation between the agents of the team during flight by attending to the distance criteria during the path-following and avoiding collision among them. For validating the investigated approaches, the proposed SIL platform uses a team of virtual UAVs based on the non-linear aerodynamic model of the Cessna 172 Skyhawk implemented in a ROS/Gazebo architecture, while the Matlab/Simulink executes of the flocking control algorithms. Simulation results demonstrated that the flocking algorithms can efficiently coordinate the underactuated UAVs teams considering their nonlinear dynamics and also the communication among all of them during the execution of different flight maneuvers.