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arXiv · 2507.01462

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
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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.

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Eneko Osaba, Estibaliz Garrote, Pablo Miranda-Rodriguez, Alessia Ciacco, Itziar Cabanes, Aitziber Mancisidor. 2025-07-02. Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0. https://arxiv.org/abs/2507.01462

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