Datasets

Industrial development is evolving towards an increased focus on human-machine collaboration, exemplified by the emergence of Industry 5.0. This new industrial paradigm prioritizes solutions centered around humans and emphasizes resilience and sustainability. A critical aspect of this collaboration is the need for robots to possess more advanced cognitive abilities, allowing for safe co-working environments with humans. Advancements in technology have enabled various methods for monitoring human behavior. Analyzing these behavioral patterns enhances efficiency and collaboration. 

My thesis introduces a setting where monitoring the operator and the robot is possible. It is achieved through a camera, an indoor positioning system, and, in the future, wearable sensors. Indicators, for example, the utilization of participants or waiting times, can represent the collaboration.

Measurements were taken with a specific focus, and the results were analyzed comprehensively—the thesis aimed to establish a connection between human activities and collaborative robots while considering human needs. The process used to achieve this objective is demonstrated through two complex games, and the design of experiments, which were then used to create and do more comprehensive experiments, is also presented.