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

TL;DR

This paper investigates hybrid quantum-classical algorithms for optimizing robotic inspection paths in Industry 4.0, demonstrating competitive solutions with faster computation times compared to classical methods.

Contribution

It introduces a quantum-assisted approach to solve complex 3D TSP variants for robotic inspection, showing potential advantages over traditional solvers.

Findings

Quantum algorithms achieve comparable solution quality.

Significantly reduced computation times.

Effective in real-world industrial scenarios.

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.