Articolo in rivista, 2022, ENG, 10.3390/app12146839
Umbrico, Alessandro and Orlandini, Andrea and Cesta, Amedeo and Faroni, Marco and Beschi, Manuel and Pedrocchi, Nicola and Scala, Andrea and Tavormina, Piervincenzo and Koukas, Spyros and Zalonis, Andreas and Fourtakas, Nikos and Kotsaris, Panagiotis Stylianos and Andronas, Dionisis and Makris, Sotiris
National Research Council of Italy, Institute of Cognitive Sciences and Technologies, 00185 Rome, Italy National Research Council of Italy, Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, 20133 Milan, Italy Dipartimento di Ingegneria Meccanica e Industriale, University of Brescia, 25123 Brescia, Italy CEMBRE S.p.A., 25135 Brescia, Italy Netcompany-Intrasoft, L1253 Luxembourg, Luxembourg Laboratory for Manufacturing Systems & Automation, University of Patras, 26500 Patras, Greece
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.
Applied sciences 12 (14)
human-robot collaboration, augmented reality, cyber physical systems, knowledge representation, planning and scheduling
Pedrocchi Nicola, Orlandini Andrea, Umbrico Alessandro, Faroni Marco, Cesta Amedeo
ISTC – Istituto di scienze e tecnologie della cognizione, STIIMA – Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato
ID: 468948
Year: 2022
Type: Articolo in rivista
Creation: 2022-07-06 13:01:31.000
Last update: 2023-06-29 10:19:17.000
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:468948
DOI: 10.3390/app12146839