Litcius/Paper detail

Design of Advanced Human–Robot Collaborative Cells for Personalized Human–Robot Collaborations

Alessandro Umbrico, Andrea Orlandini, Amedeo Cesta, Marco Faroni, Manuel Beschi, Nicola Pedrocchi, Andrea Scala, Piervincenzo Tavormina, Spyridon Koukas, Andreas Zalonis, Nikos Fourtakas, Panagiotis Stylianos Kotsaris, Dionisis Andronas, Sotiris Makris

2022Applied Sciences27 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Leverage (statistics)AdaptabilityHuman–computer interactionComputer scienceFlexibility (engineering)Software deploymentRobotKnowledge managementArtificial intelligenceSoftware engineeringEcologyStatisticsMathematicsBiologyManufacturing Process and OptimizationDigital Transformation in IndustryRobot Manipulation and Learning