Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0
Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0
著者: Eneko Osaba, Estibaliz Garrote, Pablo Miranda-Rodriguez, Alessia Ciacco, Itziar Cabanes, Aitziber Mancisidor
分類: cs.RO, cs.AI, cs.ET
原文アブストラクト
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.