Towards Smart Distributed Robotics Solution using Digital Twin

Abstract

The global COVID-19 pandemic has put a strain on the healthcare system, further compounded by the aging population and the staffing shortage. As a result, the demand for healthcare exceeds the available offer, and health professionals are forced to compensate the best they can. On the other hand, some tasks can easily be offloaded to robots. Some solutions already exist, but they are not necessarily scalable, and exhibit a very high price point. This paper outlines our vision of a new distributed robotics approach to mitigate these constraints. We propose a prototype of an autonomous robot to assist healthcare professionals (e.g., nurses) in their work – for instance, by gathering equipment and delivering water and food to give them more time for human-centric tasks. The solution incorporates the ideas of cloud-fog-edge robotics to enable AI-based control with digital twin notions to help with the training. Preliminary work is introduced on the robot platform and the framework to facilitate communication at every infrastructure layer.