Papers
9
Total Citations
269
H-Index
7
About
Maxime Thieffry is a robotics and control researcher whose work sits at the intersection of soft robotics, finite element modeling, and control theory. His research has focused on one of the field's most pressing challenges: making computationally demanding finite element methods practical for real-time simulation and closed-loop control of soft robots — inherently compliant, nonlinear systems that resist traditional control frameworks. Thieffry's most significant contributions center on reduced-order modeling strategies that preserve accuracy while dramatically cutting computational cost. His 2019 paper on dynamically closed-loop controlled soft robotic arms (87 citations) and his 2018 work on reduced-order control design (79 citations) together established a cohesive framework for dynamic soft robot control, filling a notable gap in the field's literature. He further extended this work to trajectory tracking for large-scale linear systems and developed controllability pre-verification tools to guide soft robot design before physical prototyping, replacing inefficient trial-and-error processes. His doctoral thesis, "Model-Based Dynamic Control of Soft Robots," synthesizes these contributions into a unified treatment. More recently, he has expanded his scope to cable-driven parallel robots. With over 260 cumulative citations, Thieffry's work has meaningfully advanced the computational foundations that make intelligent soft robotic systems a practical reality.
Research Focus
Key Achievements
Top Papers
- 1
- 2Control Design for Soft Robots based on Reduced Order Model79 citations · 2018
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- 5Reduced Order Control of Soft Robots with Guaranteed Stability16 citations · 2018
- 6Dynamic Control of Soft Robots15 citations · 2017
- 7
- 8Model-Based Dynamic Control of Soft Robots5 citations · 2019
- 9