Yu Dongdong

Beijing Institute of Technology, Tsinghua University

Papers

Total Citations

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About

Yu Dongdong is a rising researcher in advanced robotics and precision motion control, with key contributions spanning human-robot collaboration and ultra-precision manufacturing. His work bridges the gap between passive robotic assistance and active co-carrying systems, as demonstrated in his highly cited 2024 paper "A Hybrid Framework Based on Bio-Signal and Built-in Force Sensor for Human-Robot Active Co-Carrying" (12 citations), which proposes a novel framework integrating bio-signals with force sensors for intuitive human-robot collaboration in factory settings. This represents a significant step toward more responsive and adaptive industrial robots. In precision engineering, his 2014 work on "A cascaded iterative learning motion control scheme for an ultra-precision dual-stage actuated wafer stage" (4 citations) introduced an innovative cascaded iterative learning control approach that overcomes the limitations of standard Q-filter-based methods, achieving superior tracking performance for semiconductor manufacturing equipment. With a growing citation impact, Yu's research is increasingly recognized for its practical implications in both collaborative robotics and high-precision motion systems, positioning him as a promising contributor to next-generation automation technologies.