Cooperative Human-Machine Interaction in Industrial Environments

Recently, the concept of Human-centered automation is adopted in Human-Robot Collaboration (HRC) scenarios, where interactive manufacturing systems are designed to emphasize human activities, by relating them with Cyber-Physical Production Systems (CPPS). This research is focused on self-adaptation of industrial manipulators to the operator's physiological characteristics, which involve the correlation of different biometric signals. A collaborative environment was achieved by implementing a CPPS for this intent. The developed use case scenario consists in a simple manufacturing process, which involves a human operator and a mini robotic arm, in a joint manipulation of objects. The robotic arm assists the human operator regarding task execution, considering the worker's real-time monitoring, regarding stress and fatigue levels and motion tracking. The monitoring of the human operator serves as input for the self-adaptation of the robotic arm, namely task execution's speed, and correct operation. Presented results show that the implemented Fuzzy system can classify stress and fatigue with an accuracy of 87.8% and 74.4% respectively.