An Approach to Human-Robot Collaborative Drilling and Fastening in Aerospace Final Assembly

View Video Presentation: https://doi.org/10.2514/6.2021-0270.vid The aerospace manufacturing industry is increasingly adopting automated machinery to accomplish labor intensive tasks and to meet growing production demands. Traditionally, production floors are filled with fixed-installation robots that are not easily adapted to hanging needs. In this work, we present an approach to using a collaborative robot to complete drilling and fastening tasks that can adapt to new environments by leveraging a human operator and expert demonstrator. The human trains the robot to complete the task autonomously by defining its environment and providing the robot demonstrations on how to locate, classify, and insert fasteners into a fuselage. The system begins with no information and uses offline and online learning techniques to develop a data bank of relevant information to improve the insertion process within the workspace. We show the results of unit tests that evaluate the multiple steps to the learning-execution process and draw conclusions from our observations.