Development and Optimization of Formation Flying for Unmanned Aerial Vehicles Using Particle Swarm Optimization Based on Reciprocal Velocity Obstacles

In this article, a formation flying technique designed for a multiple unmanned aerial vehicles (multi-UAV) system to provide low-cost and efficient solution for civilian and military applications is presented. First, a modular leader-follower formation algorithm was developed to accomplish the formation flying with off-the- shelf low- cost components and sensors. Second, a proportional-integral- derivative (PID) controller was utilized for velocity control of the UAVs to maintain the tight formation. Third, a particle swarm optimization- optimized reciprocal velocity obstacles (PSO-RVO) algorithm was utilized for obstacles avoidance and collision avoidance between the UAVs while navigating, with the aid of sonar ranging sensors onboard. The formation flying algorithm developed was tested through both simulation and experiment using two quadcopters with global positioning system (GPS) signals. For the simulation, the algorithm developed was tested on a virtual quadcopter using an open- source software-in-the- loop (SITL) simulator. With the aid of the experimental test, the effectiveness of the proposed formation flying algorithm is evaluated. With a separation distance of 5 m between the UAVs, the proposed system is able to achieve an average separation error of 0.3872 m and percentage of root mean square error (RMSE) of 9.7%. Therefore, it is shown that the proposed formation flying system is very effective.