MODELING OF EMOTIONAL-ADAPTIVE INTERACTION OF COLLABORATIVE ROBOTS IN THE INDUSTRY 5.0 ENVIRONMENT BASED ON FRACTAL-NEURAL LOGIC

The article presents an approach to modeling the emotional-adaptive interaction of collaborative robots based on fractal-neural logic within Industry 5.0 concept. The proposed model combines the fractal nature of noise with deep neural networks to reproduce the dynamics of emotional states in a changing environment. The simulation demonstrates the system's ability to adaptively learn and take into account the context of interaction between agents. The results indicate the effectiveness of the approach for building flexible, emotionally sensitive robotic systems focused on cognitive-social integration. The model can be used in service, production, and social robotics to create new forms of cooperative behavior.