Mehdi Salmani Jelodar

Papers

Total Citations

H-Index

About

Mehdi Salmani Jelodar’s research centers on the design, optimization, and control of reconfigurable robotic manipulators, with a particular focus on cooperative and dual-arm systems. His major contributions lie in advancing the Dual-Arm Cam-Lock (DACL) robot—a novel class of reconfigurable manipulators where two parallel arms can lock together to enhance structural stiffness while operating redundantly for flexibility. Through his work, Jelodar developed genetic algorithm-based optimization methods to determine optimal configurations that maximize task-space force output at specific points, directly addressing the trade-off between dexterity and rigidity in robotic systems. His most cited paper, “Genetic algorithm based optimization for Dual-Arm Cam-Lock robot configuration” (2007, 3 citations), and its companion study on optimal configuration of a 4-DOF DACL manipulator (2007, 2 citations) laid foundational groundwork for reconfigurable cooperative robotics. While his citation counts are modest, these early contributions are notable for introducing computational optimization to a niche but impactful area of robot design. Jelodar’s work remains relevant for researchers exploring adaptive, high-stiffness manipulators for precision tasks in manufacturing and assembly.