Digital Twin in Modeling and Control of Collaborative Robots: Analysis, Comparison and Application Recommendations

Abstract

The work examines the Digital Twin concept as a key technological solution for modeling, simulation, and intelligent control of collaborative robots in Industry 5.0 environments. The analysis focuses on mathematical and computational methods underlying Digital Twin systems, including kinematic and dynamic models, probabilistic state estimation methods, environment representation models, sensor fusion techniques, and predictive simulation models. Their mathematical foundations, computational complexity, accuracy, scalability, and suitability for realtime control are compared. The advantages and limitations of each method are evaluated. Practical recommendations are provided for implementing Digital Twin systems in collaborative robotics, autonomous navigation, and cyber-physical production systems.