A Digital Twin-Based Intelligent Robotic Measurement System for Freeform Surface Parts

Abstract

This paper proposed a novel framework of a digital twin-based robotic measurement system for freeform surface parts, which can improve the efficiency, autonomy, and intelligence of the robotic measurement system. This framework provides core services for robotic measurement tasks including visibility computation, collision detection, sensor simulation, path planning, and 3D inspection. These services improve the adaptability and the simulation capability of digital twin-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. And case studies demonstrated the advantages of the digital twin-based robotic measurement system in terms of viewpoint planning, measurement path planning, object reconstruction, and 3D inspection.