Chenglin Dong

Tianjin University, Tianjin University of Technology

Papers

10

Total Citations

359

H-Index

8

About

Chenglin Dong is a robotics and mechanical engineering researcher whose work centers on the modeling, design, and optimization of hybrid and parallel robots for precision manufacturing applications. With a body of research accumulating over 350 citations, Dong has established himself as a significant contributor to the theoretical and practical advancement of multi-degree-of-freedom robotic systems. His most influential contributions include pioneering stiffness modeling frameworks for 5-DOF hybrid robots (96 citations) and developing innovative, visually intuitive methodologies for the type synthesis of overconstrained parallel mechanisms (61 citations). His screw theory-based semi-analytical approach to elastodynamic modeling of the Tricept robot (60 citations) has proven particularly impactful, offering practitioners a powerful tool for analyzing complex robotic architectures. Dong's research consistently bridges abstract mechanical theory with real-world machining and polishing applications, as demonstrated through his dynamic modeling work and kinematic calibration studies using laser trackers. More recently, he has extended his focus toward digital design frameworks and elasto-dynamic performance evaluation, reflecting a forward-looking integration of computational tools with robot design optimization. His sustained output across stiffness analysis, kinetostatics, and dimensional optimization makes him a valuable reference for researchers and engineers developing next-generation precision robotic systems.

Research Focus

Key Achievements

8
H-Index
10
Papers
359
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
Stiffness modeling and analysis of a novel 5-DOF hybrid robot
96 citations · 2017
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: Tianjin University, Tianjin University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago