Papers
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Total Citations
2
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About
Rong Su is an emerging researcher at the intersection of artificial intelligence, robotics, and smart manufacturing, with a focus on advancing human-robot collaboration (HRC) systems. His most notable work explores the integration of deep learning architectures with classical computational methods to solve complex problems in industrial automation. In his highly regarded study on human manipulation prediction, Su pioneered a hybrid approach that combines Long Short-Term Memory (LSTM) networks with Inverse Kinematics, enabling more accurate forecasting of human operators' upper limb trajectories in dynamic manufacturing environments. This contribution addresses a critical gap in existing model-based approaches, pushing the boundaries of how intelligent systems can anticipate and adapt to human behavior on the factory floor. While his published record is still developing — with his 2024 paper already accumulating citations shortly after release — Su's research reflects a timely and impactful direction as industries worldwide accelerate their adoption of collaborative robotics. His work holds significant promise for students and practitioners seeking to understand how AI-driven prediction models can meaningfully enhance safety, efficiency, and human-machine synergy in next-generation smart manufacturing settings.
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