Resource planning for UAV swarms based on NSGA-II

With the development of unmanned systems, the scale and application scenarios of unmanned swarms have greatly expanded. At present, the research on swarms mainly focuses on the swarm intelligent bionic strategy and the implementation of obstacle avoidance algorithms for specific task scenarios. In the process of swarm control, due to the complex natural environment and limited number of base station connections, the size of the swarm for specific task scenarios needs to be explored and studied. Different mission scenarios have different requirements for the capability of the drone. How to organize the unmanned nodes that meet the mission capability requirements, and how large the swarm size is the best for the mission completion revenue. This article mainly addresses the above two issues. Based on the target search task, the task requirements and the capability of the UAV group are formally modeled, the mapping between the task requirements and the UAV capability is matched, and the multiobjective optimization problem is solved by the NSGA-II algorithm. The unmanned nodes that meet the mission requirements are organized to form alliances. This model is also applicable to mission scenarios where area coverage is required.