Mehdi Zabihi

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About

Mehdi Zabihi is a robotics researcher whose work centers on the dynamic modeling, stability, and control of legged and acrobatic robotic systems. His key contributions lie in advancing the understanding of constrained dynamical systems, particularly through comparative analyses of modeling methods such as Kane’s and Lagrange’s approaches. Zabihi’s most cited paper, “Comparison of Kane’s and Lagrange’s Methods in Analysis of Constrained Dynamical Systems” (2020, 18 citations), provides a foundational framework for improving computational efficiency and accuracy in simulating mechanical systems with constraints. He has also made notable strides in bio-inspired robotics, including the design and control of a novel handspringing robot (2019, 10 citations) and a one-legged somersaulting robot (2018, 7 citations). These works address the hybrid dynamic challenges of hopping and flipping motions, integrating fuzzy control strategies to manage the complex stance and flight phases. Zabihi’s research is particularly impactful for students and engineers interested in nonlinear dynamics, robot locomotion, and control theory. His achievements demonstrate a clear trajectory from theoretical modeling to practical robotic applications, offering valuable insights for developing agile, high-performance robots capable of dynamic maneuvers.