Papers
5
Total Citations
68
H-Index
4
About
Sophie Tarbouriech is a leading researcher in control theory and robotics, whose work bridges the gap between theoretical rigor and practical implementation. Her primary research areas include nonlinear control systems, high-gain observers, and vision-based robotic control. Tarbouriech made a significant contribution to addressing the peaking phenomenon in high-gain observers, a critical issue in nonlinear systems, with her 2016 paper on a hybrid scheme to reduce peaking, which has garnered 30 citations. She also advanced industrial robotics through her work on the Par2 parallel robot, developing identification and vibration attenuation techniques to mitigate undesirable end-effector vibrations during high-speed pick-and-place operations—a paper that has earned 20 citations. In the domain of mobile robotics, Tarbouriech designed robust vision-based controllers for navigation and task sequencing, as demonstrated in her 2005 and 2006 papers, which introduced multicriteria image-based controllers capable of stabilizing cameras despite unknown target depth and visual constraints. Her 2010 work further expanded on visual servo control with multi-constraint satisfaction. With a career spanning over a decade, Tarbouriech’s research has been cited over 68 times, reflecting her impact on both theoretical advancements and real-world robotic applications.
Research Focus
Key Achievements
Top Papers
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- 2Identification and Vibration Attenuation for the Parallel Robot Par220 citations · 2013
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