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Enabling Manual Guidance in High-Payload Industrial Robots for Flexible Manufacturing Applications in Large Workspaces

Articolo
Data di Pubblicazione:
2025
Citazione:
Enabling Manual Guidance in High-Payload Industrial Robots for Flexible Manufacturing Applications in Large Workspaces / Avanzi La Grotta, P.; Salami, M.; Trentadue, A.; Bilancia, P.; Pellicciari, M.. - In: MACHINES. - ISSN 2075-1702. - 13:11(2025), pp. 1-15. [10.3390/machines13111016]
Abstract:
Industrial Robots (IRs) are typically employed as flexible machines to perform many types of repetitive and intensive tasks within fenced safe areas, ensuring high productivity and cost efficiency. However, their rigid programming approaches often pose challenges during cell commissioning and reset, hindering the implementation of self-reconfigurable systems. In addition, several production lines still need the presence of skilled operators to conduct assisted assembly operations and inspections. This motivates the growing interest in the development of innovative solutions for supporting safe and efficient human–robot collaborative applications. The manual guidance of the IR end-effector is a representative functionality of such collaboration, as it simplifies heavy-part manipulation and allows intuitive robot teaching and programming. The present study reports a sensor-based approach for enabling manual guidance operations with high-payload IRs and discusses its practical implementation on a production cell with an extended workspace. The setup features a KUKA robot mounted on a custom linear track actuated via Beckhoff technology to enable flexible assembly and machining operations. The developed logic and its software configuration, split into multiple control units to allow the manual guiding of both the 6-axis IR and the linear track unit, are described in detail. Finally, an experimental demonstration involving two users with different levels of expertise was conducted to evaluate the approach during target teaching on a physical cell. The results showed that the proposed manual guidance method significantly reduced task completion time by more than 55% compared with the conventional teach pendant, demonstrating the effectiveness and practical advantages of the developed framework.
Tipologia CRIS:
Articolo su rivista
Keywords:
collaborative manufacturing; human–robot interaction; industrial robot; linear track; manual guiding
Elenco autori:
Avanzi La Grotta, P.; Salami, M.; Trentadue, A.; Bilancia, P.; Pellicciari, M.
Autori di Ateneo:
Avanzi La Grotta PAOLO
BILANCIA PIETRO
PELLICCIARI Marcello
SALAMI MARTINA
TRENTADUE ANDREA
Link alla scheda completa:
https://iris.unimore.it/handle/11380/1393369
Link al Full Text:
https://iris.unimore.it//retrieve/handle/11380/1393369/945556/Machines_HandGuiding.pdf
Pubblicato in:
MACHINES
Journal
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