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

--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-T ools. 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. Advances in quantum computing are enabling problem-solving capabilities at a scale beyond brute-force classical simulation [1]. As hardware improves--with more qubits, lower error rates, and faster execution--quantum algorithm research is advancing through both theory and experimentation.