Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0
This addresses the need for efficient automation in Industry 4.0, but is incremental as it applies existing quantum methods to a specific domain problem.
This work tackled the problem of optimizing robotic inspection trajectories in industrial settings by modeling it as a 3D Traveling Salesman Problem, and found that hybrid quantum-classical algorithms achieved competitive solution quality with significantly reduced computation times compared to classical methods.
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.