Yaser Salehinia

Papers

Total Citations

H-Index

About

Yaser Salehinia is a robotics researcher whose work centers on bipedal locomotion and humanoid robot control, with a particular focus on achieving stable, adaptive walking across varied terrains. His major contributions lie in the development of hybrid control strategies that combine Central Pattern Generators (CPGs) with Zero Moment Point (ZMP) methods, addressing the fundamental challenges of dynamic gait planning—stability, speed, and smoothness. In his most cited work, "An Open Loop Walking on Different Slopes for NAO Humanoid Robot" (2012, 19 citations), Salehinia proposed a novel approach to generating joint trajectories without relying on complex 3D Cartesian space calculations, instead using polynomial interpolation to ensure continuous motion derivatives. His follow-up study, "A hybrid controller based on CPG and ZMP for biped locomotion" (2013, 10 citations), further advanced the field by integrating biological inspiration with classical stability metrics. While his citation counts reflect a focused but impactful body of work, Salehinia’s research is particularly notable for its practical application to the NAO humanoid platform, offering accessible solutions for real-world robotic walking on slopes and uneven ground—a key step toward more versatile humanoid robots.