Yadollah Farzaneh
Ferdowsi University of Mashhad, Islamic Azad University, Mashhad
Papers
5
Total Citations
50
H-Index
3
About
Yadollah Farzaneh is a robotics researcher whose work sits at the intersection of bio-inspired control, trajectory generation, and human-robot interaction. His primary research focus is the application of Central Pattern Generators (CPGs)—neural circuits that produce rhythmic movements in biological systems—to robotic locomotion and industrial manipulation. Farzaneh’s most influential contribution is a bio-inspired framework for online trajectory generation, first demonstrated on a seven-link biped robot using a Takagi–Sugeno fuzzy system (24 citations). This work, along with his development of an automated learning CPG for rhythmic patterns (9 citations), provides a foundation for robots to produce smooth, adaptive motions without pre-programmed paths. He extended this approach to industrial robots, enabling online point-to-point rhythmic movement that mimics biological efficiency (11 citations). More recently, Farzaneh has focused on exoskeleton control, designing CPG pathways for lower limbs that allow users to change walking routes in real time (3 citations). His trajectory planning research also addresses practical challenges like backlash reduction in 3-RRR manipulators (3 citations). With a career spanning over a decade, Farzaneh’s work bridges theoretical neuroscience and applied robotics, offering scalable solutions for legged robots, industrial automation, and assistive devices.
Research Focus
Key Achievements
Top Papers
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- 3New automated learning CPG for rhythmic patterns9 citations · 2012
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