Intuitive Interfaces for Human-Robot Collaboration: Handling Novel PCBs for Industrial Manufacturing

The robotic manipulation of printed circuit boards (PCBs) poses complex challenges. Moreover, the evolving requirements of the production line necessitate the introduction of new types of PCBs, thereby adding challenges during the reconfiguration of the robotic system. This work presents the implementation of intuitive interfaces designed to adapt robotic skills for handling PCBs that are novel to the system. The focus is on tasks related to manipulating PCBs, specifically ensuring stable PCB-pick-up and subsequent highly precise-PCB-placement. Consequently, a multi-modal programming framework is presented that seamlessly integrates vision-based parametrization and kinesthetic teaching, aiming to empower non-robotic experts to reconfigure robotic skills for novel PCB types, even for tasks requiring high accuracy. Additionally, to facilitate these interfaces, a hardware setup is introduced, and the robotic system’s adaptability is demonstrated in a laboratory setting during both skill configuration and execution. Finally, limitations of robotic manipulation of PCBs are discussed.