Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0

Eneko Osaba; Estibaliz Garrote; Pablo Miranda-Rodriguez; Alessia Ciacco; Itziar Cabanes; Aitziber Mancisidor

doi:10.1109/QCE65121.2025.10359

Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0

Eneko Osaba^*
, Estibaliz Garrote
, Pablo Miranda-Rodriguez
, Alessia Ciacco
, Itziar Cabanes
, Aitziber Mancisidor

^*Autor correspondiente de este trabajo

Quantum

University of Calabria

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (SciVal)

Resumen

This work explores the application of hybrid quantum-classical algorithms to optimize robotic inspection trajectories derived from Computer-Aided Design (CAD) models in industrial settings. By modeling the task as a 3D variant of the Traveling Salesman Problem-incorporating incomplete graphs and open-route constraints-This study evaluates the performance of two D-Wave-based solvers against classical methods such as GUROBI and Google OR-Tools. Results across five real-world cases demonstrate competitive solution quality with significantly reduced computation times, highlighting the potential of quantum approaches in automation under Industry 4.0.

Idioma original	Inglés
Título de la publicación alojada	Keynotes, Workshops, Posters, Panels, and Tutorials Program
Editores	Candace Culhane, Greg Byrd, Hausi Muller, Andrea Delgado, Stephan Eidenbenz
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	388-389
Número de páginas	2
ISBN (versión digital)	9798331557362
DOI	https://doi.org/10.1109/QCE65121.2025.10359
Estado	Publicada - 2025
Evento	6th IEEE International Conference on Quantum Computing and Engineering, QCE 2025 - Albuquerque, Estados Unidos Duración: 31 ago 2025 → 5 sept 2025

Serie de la publicación

Nombre	Proceedings - IEEE Quantum Week 2025, QCE 2025
Volumen	2

Conferencia

Conferencia	6th IEEE International Conference on Quantum Computing and Engineering, QCE 2025
País/Territorio	Estados Unidos
Ciudad	Albuquerque
Período	31/08/25 → 5/09/25

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 9: Industria, innovación e infraestructura

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10.1109/QCE65121.2025.10359

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Osaba, E., Garrote, E., Miranda-Rodriguez, P., Ciacco, A., Cabanes, I., & Mancisidor, A. (2025). Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0. En C. Culhane, G. Byrd, H. Muller, A. Delgado, & S. Eidenbenz (Eds.), Keynotes, Workshops, Posters, Panels, and Tutorials Program (pp. 388-389). (Proceedings - IEEE Quantum Week 2025, QCE 2025; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/QCE65121.2025.10359

Osaba, Eneko ; Garrote, Estibaliz ; Miranda-Rodriguez, Pablo et al. / Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0. Keynotes, Workshops, Posters, Panels, and Tutorials Program. editor / Candace Culhane ; Greg Byrd ; Hausi Muller ; Andrea Delgado ; Stephan Eidenbenz. Institute of Electrical and Electronics Engineers Inc., 2025. pp. 388-389 (Proceedings - IEEE Quantum Week 2025, QCE 2025).

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title = "Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0",

abstract = "This work explores the application of hybrid quantum-classical algorithms to optimize robotic inspection trajectories derived from Computer-Aided Design (CAD) models in industrial settings. By modeling the task as a 3D variant of the Traveling Salesman Problem-incorporating incomplete graphs and open-route constraints-This study evaluates the performance of two D-Wave-based solvers against classical methods such as GUROBI and Google OR-Tools. Results across five real-world cases demonstrate competitive solution quality with significantly reduced computation times, highlighting the potential of quantum approaches in automation under Industry 4.0.",

author = "Eneko Osaba and Estibaliz Garrote and Pablo Miranda-Rodriguez and Alessia Ciacco and Itziar Cabanes and Aitziber Mancisidor",

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Osaba, E , Garrote, E , Miranda-Rodriguez, P, Ciacco, A, Cabanes, I & Mancisidor, A 2025, Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0. En C Culhane, G Byrd, H Muller, A Delgado & S Eidenbenz (eds.), Keynotes, Workshops, Posters, Panels, and Tutorials Program. Proceedings - IEEE Quantum Week 2025, QCE 2025, vol. 2, Institute of Electrical and Electronics Engineers Inc., pp. 388-389, 6th IEEE International Conference on Quantum Computing and Engineering, QCE 2025, Albuquerque, Estados Unidos, 31/08/25. https://doi.org/10.1109/QCE65121.2025.10359

Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0. / Osaba, Eneko ; Garrote, Estibaliz ; Miranda-Rodriguez, Pablo et al.
Keynotes, Workshops, Posters, Panels, and Tutorials Program. ed. / Candace Culhane; Greg Byrd; Hausi Muller; Andrea Delgado; Stephan Eidenbenz. Institute of Electrical and Electronics Engineers Inc., 2025. p. 388-389 (Proceedings - IEEE Quantum Week 2025, QCE 2025; Vol. 2).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0

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AU - Miranda-Rodriguez, Pablo

AU - Ciacco, Alessia

AU - Cabanes, Itziar

AU - Mancisidor, Aitziber

PY - 2025

Y1 - 2025

N2 - This work explores the application of hybrid quantum-classical algorithms to optimize robotic inspection trajectories derived from Computer-Aided Design (CAD) models in industrial settings. By modeling the task as a 3D variant of the Traveling Salesman Problem-incorporating incomplete graphs and open-route constraints-This study evaluates the performance of two D-Wave-based solvers against classical methods such as GUROBI and Google OR-Tools. Results across five real-world cases demonstrate competitive solution quality with significantly reduced computation times, highlighting the potential of quantum approaches in automation under Industry 4.0.

AB - This work explores the application of hybrid quantum-classical algorithms to optimize robotic inspection trajectories derived from Computer-Aided Design (CAD) models in industrial settings. By modeling the task as a 3D variant of the Traveling Salesman Problem-incorporating incomplete graphs and open-route constraints-This study evaluates the performance of two D-Wave-based solvers against classical methods such as GUROBI and Google OR-Tools. Results across five real-world cases demonstrate competitive solution quality with significantly reduced computation times, highlighting the potential of quantum approaches in automation under Industry 4.0.

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Osaba E , Garrote E , Miranda-Rodriguez P, Ciacco A, Cabanes I, Mancisidor A. Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0. En Culhane C, Byrd G, Muller H, Delgado A, Eidenbenz S, editores, Keynotes, Workshops, Posters, Panels, and Tutorials Program. Institute of Electrical and Electronics Engineers Inc. 2025. p. 388-389. (Proceedings - IEEE Quantum Week 2025, QCE 2025). doi: 10.1109/QCE65121.2025.10359

Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0

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