Shaotao Chen
Papers
2
Total Citations
49
H-Index
2
About
Shaotao Chen is a leading researcher in intelligent manufacturing and industrial robotics, with a core focus on digital twin technology for precision engineering. His pioneering work addresses the critical challenge of positioning accuracy in robotic arms—a problem exacerbated by mechanical wear and transmission errors over time. Chen’s most influential contribution is the development of low-cost, digital twin-driven error compensation methods. His 2022 paper, "A Low-Cost Digital Twin-Driven Positioning Error Compensation Method for Industrial Robotic Arm" (29 citations), introduces an innovative framework that uses virtual models to correct physical positioning errors without expensive hardware upgrades. Building on this, his 2023 work, "Digital Twin-Driven 3-D Position Information Mutuality and Positioning Error Compensation for Robotic Arm" (20 citations), advances the field by enabling bidirectional information exchange between digital and physical systems, further enhancing accuracy and enabling predictive maintenance. With over 49 citations across his top papers, Chen’s research is widely recognized for its practical impact on reducing costs and improving reliability in industrial automation. His achievements position him as a key contributor to the next generation of smart, self-maintaining robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2