IoT-based simulation of flocking algorithm

Abstract

The study of animal groups’ flocking behavior is of great significance to the study of multi-agent system. Flocking algorithm is a typical algorithm for group control based on animal group behavior. The research on flocking algorithm is mature, but there is little research on the implementation of Flocking algorithm using digital twin. Digital twins, as a key technology in the direction of IoT, is potentially valuable for improving the efficiency of cloud and devices. Therefore, the main research goal of this paper is to simulate the flocking phenomenon in nature by using digital twins and flocking algorithm to realize the cooperative control of multi-agent systems under the scenarios of obstacle-free and obstacle. In this paper, the author uses digital twins and flocking algorithm to achieve simulations of animal flocking Behaviors. The final simulation results show that the Multi-agent system can converge agents and reach consensus, and finally cross the obstacles to reach the target node, which verifies the rationality and effectiveness of the algorithm. Through the way of digital twins, the burden of the intelligence body’s computation on obstacle identification can be reduced, and the synchronization efficiency of the cloud and the device can be effectively elevated, thus in a practical sense, favoring the deployment implementation.