Intelligent Computer Vision for Digital Twin and Reinforcement Learning for Assembly Line Balancing Enhancement

The aim of this Experiment is to improve the existing model maintained by the digital twin, by having robotic agents making sense of their surrounding world in order to detect inconsistencies between the real world and the digital representation. It focuses on dynamically allocating production resources to manufacturing tasks to better face uncertainties like machine failures and unavailability of operators.