Implementation of a digital twin for robotic switchgear wiring operations

This thesis investigates the implementation of a digital twin for robotic switchgear wiring op- erations, with a focus on developing a generalized system capable of handling diverse cabi- net configurations. A previous study successfully implemented a digital twin for switchgear wiring using ROS Noetic, but it was limited to a specific cabinet model. Building upon this foundation, this research extends the approach by migrating the system to ROS 2 Humble and incorporating additional cabinet data to create a more flexible and adaptable solution. The study analyzes wiring data across multiple cabinet types, aiming to develop a structured methodol- ogy that enables the system to autonomously adapt to new switchgear configurations in the future. Key contributions include integrating the UR5 manipulator with ROS 2, utilizing RViz for visualization, and refining robotic path planning to improve wiring efficiency. By enhanc- ing modularity, interoperability, and scalability, this research demonstrates how digital twins can facilitate intelligent automation in industrial wiring processes and lays the groundwork for future advancements in robotic manufacturing.