Fault-Coping Algorithm for Improving Leader–Follower Swarm-Control Algorithm of Unmanned Surface Vehicles

Abstract

This study presents a swarm-control algorithm to overcome the limitations inherent to single-object systems. The leader–follower swarm-control method was selected for its ease of mathematical interpretation and theoretical potential for the unlimited expansion of followers. However, a known drawback of this method is the risk of swarm collapse when the leader breaks down. To address this, a fault-coping algorithm was developed and supplemented to the leader–follower swarm-control method, which enabled the detection and responsive handling of failures, thereby ensuring mission continuity. Comprehensive data, including voltage, current, thruster speed, position, and heading angle were acquired and analyzed using sensors on unmanned surface vehicles (USVs) to monitor potential failures. In the case of a failure, such as thruster malfunction, the nearest USV seamlessly takes charge of the mission under the guidance of the fault-coping algorithm. The leader–follower swarm-control and fault-coping algorithms were successfully validated through actual sea area tests, which confirmed their operational efficacy. This study affirms the well-formed nature of the USV swarm formation and demonstrates the effectiveness of the fault-coping algorithm in ensuring normal mission performance under the virtual failure scenarios applied to the leader USV.