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.
@article{arxiv.2507.01462,
title = {Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0},
author = {Eneko Osaba and Estibaliz Garrote and Pablo Miranda-Rodriguez and Alessia Ciacco and Itziar Cabanes and Aitziber Mancisidor},
journal= {arXiv preprint arXiv:2507.01462},
year = {2025}
}
Comments
2 pages, 1 figure, paper accepted for presentation at the IEEE International Conference on Quantum Computing and Engineering (QCE)