Mohsen Omidi
Papers
5
Total Citations
43
H-Index
4
About
Mohsen Omidi is a researcher working at the intersection of human-robot collaboration, ergonomics, and assistive technologies, with particular expertise in brain-computer interfaces (BCI), augmented reality, and task allocation frameworks. His work addresses pressing real-world challenges, from reducing workplace musculoskeletal disorders to enhancing autonomy for individuals with physical disabilities. Omidi's most cited contribution, a hierarchical finite-state machine-based task allocation framework (2022, 14 citations), demonstrates how intelligent human-robot collaboration can meaningfully reduce worker injury risks in manufacturing environments. Complementing this, his particle swarm optimization approach to postural ergonomics (2023, 9 citations) offers practical computational solutions to workload distribution in collaborative settings. A distinctive strand of his research integrates BCI technology with eye tracking and augmented reality to create shared robot control systems, work that has quickly gained traction with 11 and 8 citations respectively since 2024. These systems hold significant promise for empowering users with motor disabilities to control assistive robots through mental imagery and gaze alone. More recently, Omidi has turned his attention to safety and trust dynamics in human-robot collaboration through augmented reality warning systems. Collectively, his growing citation record reflects an innovative and socially impactful research agenda bridging industrial ergonomics and advanced human-machine interaction.
Research Focus
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Top Papers
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