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

^*Corresponding author for this work

Quantum

University of Calabria

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Keynotes, Workshops, Posters, Panels, and Tutorials Program
Editors	Candace Culhane, Greg Byrd, Hausi Muller, Andrea Delgado, Stephan Eidenbenz
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	388-389
Number of pages	2
ISBN (Electronic)	9798331557362
DOIs	https://doi.org/10.1109/QCE65121.2025.10359
Publication status	Published - 2025
Event	6th IEEE International Conference on Quantum Computing and Engineering, QCE 2025 - Albuquerque, United States Duration: 31 Aug 2025 → 5 Sept 2025

Publication series

Name	Proceedings - IEEE Quantum Week 2025, QCE 2025
Volume	2

Conference

Conference	6th IEEE International Conference on Quantum Computing and Engineering, QCE 2025
Country/Territory	United States
City	Albuquerque
Period	31/08/25 → 5/09/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access to Document

10.1109/QCE65121.2025.10359

Cite this

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. In 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).

@inproceedings{b75282e680f94a4fb786e260b28fd168,

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",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 6th IEEE International Conference on Quantum Computing and Engineering, QCE 2025 ; Conference date: 31-08-2025 Through 05-09-2025",

year = "2025",

doi = "10.1109/QCE65121.2025.10359",

language = "English",

series = "Proceedings - IEEE Quantum Week 2025, QCE 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "388--389",

editor = "Candace Culhane and Greg Byrd and Hausi Muller and Andrea Delgado and Stephan Eidenbenz",

booktitle = "Keynotes, Workshops, Posters, Panels, and Tutorials Program",

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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. in 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, United States, 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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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. In Culhane C, Byrd G, Muller H, Delgado A, Eidenbenz S, editors, 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

Abstract

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