用量子算法优化工业质检机器人路径，提速降耗。
Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0
- 将3D巡检路径建模为带不完整图和开放路线的旅行商问题。
- 在5个真实场景中，量子求解器比经典方法快数倍，结果相当。
- 适合关注智能制造与量子计算融合的工程师和研究者。
本文探讨了混合量子-经典算法在工业4.0环境下，基于计算机辅助设计（CAD）模型优化机器人质检路径的应用。通过将任务建模为包含不完整图与开放路线约束的三维旅行商问题，本研究对比了两种基于D-Wave的求解器与经典方法（如GUROBI和Google OR-Tools）的性能。在五个实际案例中的实验表明，量子求解器在计算时间上显著优于经典方法，同时保持了具有竞争力的解决方案质量，展现出量子计算在自动化领域的应用潜力。
原文摘要 · Abstract (English)
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.
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