Tong Ge

Shanghai Jiao Tong University

Papers

9

Total Citations

104

H-Index

7

About

Dr. Tong Ge is a leading researcher in the dynamic modeling and control of underwater and robotic systems, with a particular focus on bio-inspired and reconfigurable platforms. His major contributions lie in the application of Kane’s method to derive accurate, incremental dynamic models for complex robotic systems, including remotely operated vehicles (ROVs) with manipulators, underwater snake-like robots, and quadruped walking robots. This work has been foundational for advancing the simulation and control of these systems. His most cited paper, "Parametric identification and structure searching for underwater vehicle model using symbolic regression" (2016, 34 citations), showcases his innovative approach to system identification. Dr. Ge has also made significant strides in adaptive control, developing novel adaptive PID controllers for robotic manipulators that do not require constraints on control gains (2021, 13 citations). His research on central pattern generator (CPG)-based gait control for quadruped robots and simulation platforms for underwater snake-like robots further demonstrates his impact on the field, with multiple papers receiving 7-8 citations each. Through his work, Dr. Ge has provided essential tools and methodologies for the design and control of next-generation autonomous underwater and terrestrial robots.

Research Focus

Key Achievements

7
H-Index
9
Papers
104
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Parametric identification and structure searching for underwater vehicle model using symbolic regression
34 citations · 2016
📈 Most Prolific Year: 2014 (4 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Shanghai Jiao Tong University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago