Cooperative formation and navigation methods for distributed unmanned surface vehicle systems with sensing information

This paper investigates distributed strategy to improve the control efficiency for unmanned surface vehicles (USVs) in cooperative coexistence. We propose a distributed method of cooperative formation control and navigation with sensing information under motion constraints. Firstly, a distributed unmanned surface vehicle (USV) system model is developed using the dynamics model of the USVs. Local coordinates are employed to optimize the heading vector, enabling the USVs to navigate toward their destination while maintaining a specific formation. Subsequently, a control gain optimization model is formulated for the distributed USV system based on motion constraints. Lastly, the sensing information-based gain matrix design involves no-convex optimization, which is solved via a semidefinite relaxation (SDR) approach. Numerical results validate that the proposed approach significantly improves the control efficiency of the USV system and reduces communication overhead.