A Study of Formation Control and Trajectory Replication Algorithms for Unmanned Systems of Industrial Robots

With the rapid development of industrial automation technology, industrial robots and unmanned systems are increasingly used in production lines. Formation control and trajectory reproduction are the key technologies for these systems to work together efficiently. The purpose of this paper is to study the formation control strategy and trajectory reproduction algorithm of industrial robot unmanned system, so as to improve production efficiency and system stability. In this paper, a trajectory prediction and reproduction method is proposed in the aspect of trajectory reproduction algorithm. In this method, a formation algorithm based on graph theory and second-order consistency is proposed to obtain stable inverted “V” formation through training model. The information interaction channel between the agents in the formation of the unmanned system is established through graph theory, and then the dynamic equation of the formation of the unmanned system is established according to the consistency theory, and then the accurate prediction and reproduction of the trajectory of the robot and the unmanned system are realized. At the same time, the paper also discusses how to dynamically adjust and optimize the prediction trajectory with real-time perception data to adapt to the complex and changing production environment. The simulation results show that the formation control strategy and trajectory reproduction algorithm studied in this paper show good performance and stability in practical applications. These research results are of great significance for improving the operation efficiency of industrial robots and reducing production costs, and provide strong support for the construction of intelligent factories in the future.