LAUSR

This article proposed a novel framework of a digital twin (DT)-based robotic measurement system (RMS) for freeform surface parts, which can improve the efficiency, autonomy, and intelligence of the RMS. This framework provides core services for robotic measurement tasks, including visibility computation, collision detection, sensor simulation, path planning, and 3-D inspection. These services improve the adaptability and the simulation capability of the DT-based robot measurement system for freeform surface parts. Based on the proposed framework, an effective viewpoint planning method combining viewpoint sampling strategy and nest-best-view planner (VS-NBV) for freeform surface parts is proposed and verified. Case studies demonstrated the advantages of the DT-based RMS in terms of viewpoint planning, measurement path planning, object reconstruction, and 3-D inspection.