Utilising Industry 4.0 Technologies to Enhance Robotic Capability for Aerospace Assembly

This paper presents the findings of an experimental test program integrating a Universal Robot and a laser tracking system in order to quantify the accuracy and positional drift of the robot over time. The approach has enabled a direct comparison between positional data for the tool centre point (TCP) location and equivalent measurements taken by the laser tracking system. The results quantify the positional error and drift of the TCP and investigate whether any robot controller outputs may have a significant effect on the error and drift. The relevance of the relations is presented in the context of robotic error compensation using artificial neural network algorithms, and how this research may contribute to an improvement in their performance to enhance robotic capability for aerospace assembly.