A Review on Digital Twin for Robotics in Smart Manufacturing
Xinquan Liang, Rui Xiao, Jingbing Zhang
Abstract
As one of the key enablers of Industry 4.0, robotics enabled automation has been increasingly deployed not only to perform dangerous, dirty, dull, and repetitive tasks, but also to support and augment human beings to address challenges associated with ageing population and labor shortages. However, the design, development, deployment, commissioning, and maintenance of robotics systems have never been trivial tasks, especially for complex robotics systems consisting of multiple heterogenous robots and other subsystems, such as manufacturing equipment, sensors, Internet of Things (IoT) gateways, smart infrastructure devices, and so on. Digital twin (DT) as a merging technology has been attracting great attentions from both researchers and industrial practitioners. Digital twin for robotics has been studied for smart manufacturing, ranging from robot-human interaction, real-time product/process inspection, production optimization, and so on. This paper provides an initial review of literatures related to digital twin for robotics. The literatures are reviewed and categorized by the enabling technologies that support the DT development, and how the DT is applied and implemented in different system life cycle stages. This review aims to provide insights of the current research work and highlight key challenges that should be addressed by future research.