Unmanned equipment and systems, represented by Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs), are a promising area of research. Based on intelligence and informatics, they can efficiently transmit tactical battlefield information and provide real-time network access for new equipment updates, which is an effective way to navigate complex environments and enhance synergy capabilities. Unmanned aerial vehicles have maneuverability advantages. Unmanned surface equipment, represented by unmanned ships, has advantages in terms of carrying capacity and long-term self-sustainment. Collaborative control and planning of multiple unmanned platforms is a popular topic in intelligent unmanned system control research. In the context of informationization, network, and system confrontation, the coordination of multiple unmanned platforms is used to enable information and resource sharing throughout the entire unmanned system. This maximizes the utilization of their respective advantages and improves the operational effectiveness of the entire system, which has significant theoretical and practical value. Based on years of research, this paper studies the key theories and technical problems of cooperative path planning and formation control for multiple unmanned platforms, using UAVs and USVs as examples, and provides corresponding control algorithms and simulations.

Unmanned equipment and systems, represented by Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs), are a promising area of research. Based on intelligence and informatics, they can efficiently transmit tactical battlefield information and provide real-time network access for new equipment updates, which is an effective way to navigate complex environments and enhance synergy capabilities. Unmanned aerial vehicles have maneuverability advantages. Unmanned surface equipment, represented by unmanned ships, has advantages in terms of carrying capacity and long-term self-sustainment. Collaborative control and planning of multiple unmanned platforms is a popular topic in intelligent unmanned system control research. In the context of informationization, network, and system confrontation, the coordination of multiple unmanned platforms is used to enable information and resource sharing throughout the entire unmanned system. This maximizes the utilization of their respective advantages and improves the operational effectiveness of the entire system, which has significant theoretical and practical value. Based on years of research, this paper studies the key theories and technical problems of cooperative path planning and formation control for multiple unmanned platforms, using UAVs and USVs as examples, and provides corresponding control algorithms and simulations.

Unmanned equipment and systems, represented by Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs), are a promising area of research. Based on intelligence and informatics, they can efficiently transmit tactical battlefield information and provide real-time network access for new equipment updates, which is an effective way to navigate complex environments and enhance synergy capabilities. Unmanned aerial vehicles have maneuverability advantages. Unmanned surface equipment, represented by unmanned ships, has advantages in terms of carrying capacity and long-term self-sustainment. Collaborative control and planning of multiple unmanned platforms is a popular topic in intelligent unmanned system control research. In the context of informationization, network, and system confrontation, the coordination of multiple unmanned platforms is used to enable information and resource sharing throughout the entire unmanned system. This maximizes the utilization of their respective advantages and improves the operational effectiveness of the entire system, which has significant theoretical and practical value. Based on years of research, this paper studies the key theories and technical problems of cooperative path planning and formation control for multiple unmanned platforms, using UAVs and USVs as examples, and provides corresponding control algorithms and simulations.