Mostafa Salehi

Qazvin Islamic Azad University, University of Tehran

Papers

Total Citations

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About

Mostafa Salehi is a robotics researcher whose work centers on motion planning, evolutionary computation, and autonomous robot locomotion. His research focuses particularly on humanoid and biped robots, where he has tackled one of the field's most persistent challenges: generating stable, human-like walking gaits. Salehi has made notable contributions by applying bio-inspired optimization techniques — including Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) — to Central Pattern Generator (CPG) models, enabling more efficient and naturalistic joint trajectory generation in biped robots. His 2013 paper on PSO-based joint trajectory generation has garnered 11 citations, establishing it as his most recognized contribution to the field. Building on this foundation, he extended his comparative analysis to evaluate both GA and PSO approaches for humanoid walk pattern planning, offering researchers practical insights into algorithmic performance trade-offs. Salehi also broadened his scope to mobile robotics, applying Differential Evolution optimization to Ferguson spline-based path planning for soccer robots, demonstrating versatility across robotic platforms. His body of work provides valuable computational frameworks for researchers working at the intersection of evolutionary algorithms and robotic motion control.