Cyber-Physical Systems constitute one of the core concepts in Industry 4.0 aiming at realizing production systems that combine the efforts from human workers, robots and intelligent entities. This is particularly true in Human-Robot Collaboration manufacturing where a tight peer-to-peer interaction between humans and (intelligent) autonomous robots is necessary. Such production systems need a holistic integration along different levels of abstraction and coordination for deploying effective and safe control solutions. We propose the use of novel Artificial Intelligence technologies to enhance flexibility and adaptability of these collaborative systems. Our aim is to advance the classical human-aware paradigm that considers the worker as an anonymous acting entity, in favour of a user-aware paradigm, that considers a worker as profiled user characterized with a number of specific features influencing the "shape" of the collaboration.
Industry 4.0 is pushing forward the need for symbiotic interactions between physical and virtual entities of production environments to realize increasingly flexible and customizable production processes. This holds especially for human–robot collaboration in manufacturing, which needs continuous interaction between humans and robots. The coexistence of human and autonomous robotic agents raises several methodological and technological challenges for the design of effective, safe, and reliable control paradigms. This work proposes the integration of novel technologies from Artificial Intelligence, Control and Augmented Reality to enhance the flexibility and adaptability of collaborative systems. We present the basis to advance the classical human-aware control paradigm in favor of a user-aware control paradigm and thus personalize and adapt the synthesis and execution of collaborative processes following a user-centric approach. We leverage a manufacturing case study to show a possible deployment of the proposed framework in a real-world industrial scenario.
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