Flocking Control under Virtual Leader of USVs with Obstacle Avoidance
Yuanhui Wang, Weijie Xie, Xiaoyun Zhang · 2020
It focuses on solving the problem of autonomous obstacle avoidance for unmanned surface vehicles(USVs) formation mission. Firstly, a three-degree-of-freedom kinematics and dynamic model of USV is established. Secondly, the flocking algorithm is used to solve the problem of autonomous formation control for USVs. Considering the flocking algorithm is generally applied to particle-based model, it can't be directly applied to underactuated USVs. Thus, a virtual force point is introduced and a force analysis is carried out, which converts the control inputs in the flocking algorithm into the longitudinal control and heading control. In this case, it can achieve the autonomous formation of the USVs and the purpose of tracking virtual leader. Thirdly, combining obstacle avoidance algorithm based on potential function with flocking algorithm to achieve obstacle avoidance for the formation control. Finally, the effectiveness of the algorithm and model is verified by simulation experiments.