Nolwenn Briquet-Kerestedjian
Maison de la Simulation, Centre National de la Recherche Scientifique, Université Paris-Saclay, Laboratoire des signaux et systèmes
Papers
4
Total Citations
46
H-Index
3
About
Nolwenn Briquet-Kerestedjian is a leading researcher in physical human-robot interaction (pHRI), with a primary focus on the safety and reliability of collaborative robotic manipulators. Her work addresses a critical challenge: enabling robots to distinguish between intended human contact and accidental impacts in real time. She pioneered the use of neural networks for classifying human-robot contact situations (2019, 29 citations), offering a state-of-the-art framework that allows collaborative robots to respond appropriately to different types of physical interaction. Her foundational research on generalized momentum-based observers for impact detection (2017, 12 citations) provides essential guidelines for designing robust detection systems under characterized uncertainties. She further advanced the field by quantifying the errors introduced by model uncertainties in impact detection methods (2016, 3 citations) and developing stochastic observer designs that account for these uncertainties (2017, 2 citations). Briquet-Kerestedjian’s contributions are vital for ensuring safe and efficient operation in environments where humans and robots work side by side, making her a key figure in the development of next-generation collaborative robotics.
Research Focus
Key Achievements
Top Papers
- 1Using Neural Networks for Classifying Human-Robot Contact Situations29 citations · 2019
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