Digital twin-enabled advance execution for human-robot collaborative assembly

Abstract

A reliable human-robot workcell relies on accurate and nearly real-time updated models, especially in a constrained yet dynamic environment. This paper investigates digital twin-driven human-robot collaborative assembly enabled by function blocks. Leveraging sensor data, digital models are developed to precisely mimic physical human-robot collaborative settings supported by a digital-twin architecture. An advance-execution twin system based on the current status through real-time condition monitoring performs assembly planning and adaptive robot control using a network of function blocks. An augmented reality-based interaction method using HoloLens further facilitates human-centric assembly. An engine-assembly case study is performed to validate the effectiveness of the system.