MATHEMATICAL MODEL OF LOCAL DECISION-MAKING FOR COLLABORATIVE ROBOTS USING EDGE COMPUTING

The article presents a mathematical model of local decision-making for collaborative robots using Edge Computing technologies. The proposed approach allows agents to effectively find optimal or approximately optimal routes in an environment with moderate density obstacles without centralized control. The simulation confirmed the system's ability to dynamically adapt and high resistance to changes in external conditions. The results of the study demonstrate the prospects for using local strategies to increase the autonomy, speed, and scalability of multi-robot systems. The conclusions obtained open up opportunities for further development of hybrid control algorithms, integration of machine learning methods, and application in real production and service environments.