Papers
1
Total Citations
4
H-Index
1
About
Olivier Buttelli is a researcher whose work lies at the intersection of biomechanics, human movement analysis, and control theory. His primary research areas include gait analysis, optimal control, and the modeling of human locomotion. Buttelli’s major contribution is the development of a novel framework that bridges human movement science and robotics: he proposed using optimality criteria imputed from human data to analyze natural and fast gait tasks. By modeling these tasks as nonlinear optimal control problems and applying nonlinear model predictive control—a technique more commonly used in humanoid robotics—he created an efficient, automatic tool for understanding human walking. This innovative approach allows researchers to decode the underlying principles governing human gait, offering insights that can inform both rehabilitation and robotic design. His most-cited paper, "Gait analysis using optimality criteria imputed from human data" (2017), has garnered 4 citations, reflecting its niche but foundational impact in the field. Buttelli’s work is notable for its interdisciplinary nature, demonstrating how concepts from robotics can illuminate human physiology, and it stands as a valuable resource for students and researchers exploring the computational modeling of movement.
Research Focus
Key Achievements
Top Papers
- 1Gait analysis using optimality criteria imputed from human data4 citations · 2017