SEMINAR: Identification of Legged Locomotion via Model-Based and Data-Driven Approaches, by Dr. İsmail Uyanık (March 23, 2018)
March 7, 2018
Dr. Ismail Iyanik will give a seminar on Friday, March 23, 2018 at 13:30 in the Conference Hall of our department. The title of the talk is 'Identification of Legged Locomotion via Model-Based and Data-Driven Approaches'.
All interested are invited.

The abstract and a short biography of the speaker are as follows.

The ultimate promise of legged locomotion on rough terrain led to both construction of various legged morphologies as well as many mathematical models to describe their underlying dynamics. However, data-driven modeling and analysis of legged locomotion is still in its infancy and such tools are fundamental for complementing mathematical models towards understanding ‘more complex’ legged locomotor systems. This talk covers our efforts on (1) developing mathematical models for the identification and control of legged locomotion with experimental evidence on a one-legged hopping robot platform, (2) adopting a data-driven system identification approach to obtain input—output representation of legged locomotion around a stable periodic orbit as a linear time-periodic (LTP) system and (3) developing frequency-domain subspace identification methods for LTP systems towards estimating state-space models of legged locomotion.

Short Bio
Dr. Ismail Uyanik is a postdoctoral researcher in Laboratory of Computational Sensing and Robotics (LCSR) at Johns Hopkins University. He received his Ph.D. degree in Electrical and Electronics Engineering from Bilkent University in May 2017. Throughout his Ph.D. studies at Bilkent, he worked on developing model-based and data-driven system identification methods for the analysis and control of legged locomotion. He also received his B.Sc. and M.Sc. degrees from the same department in June 2009 and August 2011, respectively. His current research focuses on discovering the principles of animal locomotion by developing novel techniques in the areas of system identification theory, computational neuroscience and robotics. He is also a recipient of Aselsan Ph.D. Fellowship, which recognizes and supports academic excellence in Aselsan’s prominent research areas.