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About

Qinglin Qi is a leading researcher in the field of intelligent manufacturing and human–robot collaboration, with a particular focus on the integration of digital twin technologies. His work centers on developing adaptive, real-time systems that enhance the synergy between human workers and robotic agents in complex industrial environments. Qi’s major contributions include the proposal of a consistency method for digital twin models in human-robot collaboration, which ensures that virtual simulations accurately reflect physical processes, a foundational concept that has garnered 53 citations. He further advanced this area with a digital twin–based environment-adaptive assignment method, enabling dynamic task allocation that responds to changing conditions, a work that has already earned 11 citations. Additionally, Qi has addressed practical challenges in aerospace maintenance through a path planning method for robot-aided aero-engine fleet inspection, incorporating a resource reuse strategy to optimize multi-robot formations. His research is notable for bridging theoretical frameworks with real-world applications, particularly in safety-critical and flexible manufacturing settings. With a growing citation impact and a clear trajectory toward more intelligent, adaptive collaboration systems, Qi’s work is shaping the future of human–robot interaction in industry.