Ahmad Gazar
Papers
5
Total Citations
22
H-Index
2
About
Ahmad Gazar is a researcher advancing the control and motion generation of legged robots, with a focus on floating base systems and contact-rich locomotion. His work addresses critical challenges in nonlinear control, state estimation, and trajectory optimization under uncertainty. Gazar’s most cited paper (2020, 12 citations) introduces jerk control for floating base systems using contact-stable parameterized force feedback, overcoming discontinuities in quadratic programming-based controllers. He further explores the underexploited use of torque measurement in centroidal state estimation (2023, 4 citations), enhancing robot awareness of its dynamics. Gazar has also pioneered nonlinear stochastic trajectory optimization for centroidal momentum motion (2023) and conducted comparative studies on stochastic and robust MPC for bipedal locomotion (2021, 2 citations), analyzing robustness and performance trade-offs. His recent work on multi-contact stochastic predictive control (2023) addresses contact location uncertainties, a critical step toward reliable locomotion in real-world environments. With a growing citation record and contributions that bridge control theory and practical robotics, Gazar is shaping the future of resilient, uncertainty-aware legged robot autonomy.
Research Focus
Key Achievements
Top Papers
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- 2On the Use of Torque Measurement in Centroidal State Estimation4 citations · 2023
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