A consistency method for digital twin model of human-robot collaboration

Abstract

Human-robot collaboration, which strives to use the best skills of humans and robots, shows board application prospects in meeting efficiency and economy requirements in various fields. As an effective method to realize physical-virtual interaction, digital twin plays a critical role in enhancing the perception and interaction in human-robot collaboration. Based on real-time interaction, digital twin reflects the physical states and further makes dynamic decisions. However, there are still some difficulties in the dynamic implementation of digital twin in human-robot collaboration. A vital issue is how to build the digital twin model to describe the physical elements in the collaborative scenario and the collaboration relationship. Moreover, how to keep the model consistency is also an important problem to be solved. In order to tackle the above problems, the four-tuple digital twin model of human-robot collaboration is firstly introduced in this paper, which includes the robot model, human model, collaborative environment model and collaboration relation model. Then, a model consistency method is further proposed, which considers two types of inconsistencies caused by model structure and model parameter, and the implementation of the above two aspects is illustrated in detail. Finally, a case study is carried out to show the feasibility of the proposed method.