Integration of an exoskeleton robotic system into a digital twin for industrial manufacturing applications

Industry 4.0 has underscored the importance of human–robot collaboration (HRC), necessitating an efficient integration of human workers and robots to achieve high-productivity manufacturing. Traditional HRC-related teaching operations rely on intuitive tools, such as a teach pendant, but are effort-intensive and require personnel with specialized skills, particularly those who use collaborative robots in manufacturing. Thus, end-effector haptic devices that offer real-time tactile feedback and easy manipulation are being explored to address these issues. However, such devices have limitations in capturing the experiential movement of users and user-friendly haptic devices that are intuitive and convenient to operate are required. Recently, the integration of HRC and digital twins for human-involved manufacturing processes is being studied. Digital twin technology is used to seamlessly connect the physical and virtual domains using virtual models for monitoring the production process and enhancing the accuracy of operational process reconfiguration. However, most teaching devices that are interfaced with digital twins in manufacturing process still demand personnel with specialized training for their operation. To address these challenges, a novel framework is proposed herein that links an exoskeleton-type robotic system with the digital twin of a collaborative robot in manufacturing processes, effectively expediting robotic task instructions. The interactions between human users and digital twins, and that between digital twins and a collaborative robot, considerably enhance our understanding of human involvement in manufacturing processes and the execution of tasks by collaborative robots. This framework comprises three subsystems: a human operator outfitted with an exoskeleton-type robot and a virtual reality (VR) device, a digital twin, and a collaborative robot. The human operator interacts with the virtual robot within the digital twin via the VR device and exoskeleton robot, whereas the collaborative robot executes the given task and transmits the measured sensor information into the digital twin. Robot tracking in the experiment and usability study of a pick-and-place process performed on the proposed framework indicates that the proposed system enhances the ease of learning and intuitiveness to human operators than the traditional teaching methods in manufacturing processes.