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About

Masoud Ghanbari is a leading researcher in the field of cable-driven parallel manipulators (CDPMs), with a primary focus on enhancing the safety, dynamics, and sensory accuracy of these robotic systems. His most impactful work, "Rapid and safe wire tension distribution scheme for redundant cable-driven parallel manipulators" (2021, 14 citations), introduces a non-iterative analytical approach that ensures safe wire tension distribution while tracking desired trajectories—a critical contribution for preventing system failures in redundant CDPMs. Ghanbari’s research also addresses the explicit dynamics of redundant parallel cable robots (2018, 10 citations), providing foundational insights into their motion control. In his experimental work on the RoboCab platform (2016, 4 citations), he pioneered multisensor data fusion to overcome cable flexibility and pulley rotation issues, significantly improving feedback accuracy. Further advancing the field, his 2017 study on optimal redundancy resolution schemes (3 citations) offers experimental validation of control strategies for stability and position control. With a career dedicated to bridging theoretical dynamics and practical implementation, Ghanbari’s contributions are essential for developing reliable, high-performance cable-driven robots in industrial and research applications.