Intelligent Planning Modeling and Optimization of UAV Cluster Based on Multi-Objective Optimization Algorithm

As a flight tool integrating carrier and reconnaissance, unmanned aerial vehicles (UAVs) are applied in various fields. In recent years, mission planning and path optimization have become the most important research focuses in the field of UAVs. With the continuous maturity of artificial intelligence technology, various search algorithms have been applied in the field of unmanned aerial vehicles. However, these algorithms have certain defects, which lead to problems, such as large search volume and low efficiency in task planning, and cannot meet the requirements of path planning. The objective optimization algorithm has a good performance in solving optimization problems. In this paper, the intelligent planning model of UAV cluster was established based on multi-objective optimization algorithm, and its path is optimized. In the aspect of modeling, this paper studied and analyzed online task planning, search rules and cluster formation control using an agent-based intelligent modeling method. For mission planning and optimization, it combined multi-objective optimization algorithm to build the model from three aspects of mission allocation, route planning and planning evaluation. The final simulation results showed that the UAV cluster intelligent planning modeling method and path optimization method based on multi-objective optimization algorithm met the requirements of route design and improved the path search efficiency with 2.26% task completion satisfaction.