Research on Task Assignment of Firefighting UAVs Based on E-CARGO Model

Firefighting UAV technology has become one of the core tools of modern firefighting operations, and its mission execution is constantly expanding in scale and complexity. In the face of this development, it has become even more critical to find an efficient way to ensure that drones can be assigned to perform their most suitable tasks. In this study, we used the Environment-Class, Agent, Role, Group, and Object (E-CARGO) model to systematically analyze the task assignment (FDTA) problem of firefighting drones, and introduced an enhanced whale optimization algorithm (EWOA) to optimize the path planning in the FDTA problem. Finally, simulation experiments are carried out under diverse terrain conditions to demonstrate the efficiency and fast response ability of the improved algorithm under different workloads and environmental conditions.