Ebrahim Yazdi
Papers
3
Total Citations
20
H-Index
3
About
Ebrahim Yazdi is a researcher specializing in bipedal locomotion and evolutionary robotics, with a focus on optimizing walking gaits for humanoid robots. His work centers on applying bio-inspired algorithms and neural controllers to achieve stable, efficient biped walking—a critical challenge in robotics. Yazdi’s most-cited paper, "Evolution of Biped Locomotion Using Bees Algorithm, Based On Truncated Fourier Series" (2010, 8 citations), introduces a Fourier series approach to generate stable locomotion for an NAO biped robot in a RoboCup simulation environment. He further advanced the field with "Evolution of Biped Walking Using Neural Oscillators Controller and Harmony Search Algorithm Optimizer" (2010, 7 citations), which employs Matsuoka neural oscillators to produce rhythmic control signals, and "A new biped locomotion involving arms swing based on neural network with harmony search optimizer" (2011, 5 citations), incorporating arm swing dynamics for enhanced stability and speed. Collectively, his contributions demonstrate novel model-free methods that integrate swarm intelligence and harmonic optimization, offering practical solutions for humanoid robotics. With a total of 20 citations across his key works, Yazdi’s research provides foundational insights for students and engineers exploring evolutionary computation and adaptive control in locomotion systems.
Research Focus
Key Achievements
Top Papers
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