Autonomous robotic 3D scanning for smart factory planning

3D scanning is an indispensable tool in industrial applications, enabling the precise digital replication of complex objects and environments to revolutionize crucial tasks in factory planning such as quality control, factory design, and overall efficiency. However, mainstream 3D scanning approaches such as structured light, 3D laser triangulation, and photogrammetry are often limited by their need for human intervention, operation, and oversight, leading to significant potential errors. To address this challenge, this paper proposes a mobile ground robotic scanning system to enable the quick, robust, and precise 3D scanning of large-scale industrial environments for smart factory planning. Through a simulation of our developed ground mobile robotic system, we demonstrate the potential of NVIDIA Isaac Sim to serve as a platform for the efficient development, prototyping, and testing of large-scale industrial robotic 3D scanning frameworks.