Digital twins for human-assistive robot teams in ambient assisted living

Jialin Chen, Jérémie Clos, Dominic Price, Praminda Caleb-Solly

Abstract: Digital twins are virtual replicas of physical systems that simulate real-world scenarios to optimize system performance, reduce physical losses, and ensure user safety. Although digital twins have been widely adopted in industrial settings, there is a lack of research on digital twins in everyday life scenarios. This report presents research aimed at developing a human-assistive robot interaction digital twin system. Our objective is to construct and utilize human biomechanical models of people using assistive devices and apply machine learning for recognition of impaired mobility, simulating edge scenarios to ensure the safety of human-assistive robot interaction prior to actual deployment. This research contributes to the advancement of digital twin technology to enhance the safety of assistive robots in the real-world.