RESEARCH OF ALGORITHMS OF FLOCK BEHAVIOR IN NATURE FOR THE POSSIBILITY OF APPLICATION IN GROUP FLIGHTS OF UNMANNED AIRCRAFT

Abstract

The article carried out a detailed analysis of the algorithms of the behavior of groups of natural formations, such as swarms of bees, fish and birds, which are able to act as a single unit in the natural environment. The ability of individuals to successfully coordinate their actions in groups was studied. One of the key features of these natural systems is their ability to coordinate and cooperate. Swarms of bees, shoals of fish, and flocks of birds can perform complex collective actions such as locomotion, hunting, gathering food, and solve a variety of tasks as a single, integrated system. Based on the analysis of the natural mechanisms underlying interaction algorithms, the possibility of application in various fields, such as the field of informatics and robotics, is considered. In computer science, using an analogy with swarm behavior can be important for optimizing computer networks, developing data routing algorithms, and solving distributed computing problems. In robotics, these algorithms can be used to create unmanned aerial vehicles (UAVs) that are capable of operating as swarm particles. The application of these algorithms will allow the development of UAVs that can effectively coordinate their actions, perform search and rescue, monitoring or other tasks in a group mode. This can be essential for applications in areas such as civil aviation, security, environmental monitoring and many others. The application of these algorithms in the management of elements of transport systems has been studied. Large swarms of bees, shoals of fish, and flocks of birds demonstrate the ability to move efficiently and coordinate under conditions of limited space and resources. A comparative analysis of swarm particle interaction algorithms was carried out and practical recommendations were given for the application of one or another algorithm in different conditions of UAV group flight. The obtained research results can be applied in the development of control systems for individual unmanned aerial vehicles that perform tasks individually and in a group.