Papers

10

Total Citations

242

H-Index

7

About

S. M. Mizanoor Rahman is a prominent researcher specializing in human-robot collaboration (HRC), autonomous systems, and intelligent manufacturing. His work sits at the intersection of robotics, cognitive systems, and industrial automation, with a particular focus on building effective partnerships between humans and robots in flexible manufacturing environments. Rahman's most influential contribution — "Mutual trust-based subtask allocation for human–robot collaboration" (2018, 118 citations) — pioneered frameworks for dynamically distributing tasks between humans and robots based on mutual trust, a concept he has refined across multiple studies. His development of regret-based autonomy allocation schemes addresses a critical challenge in collaborative robotics: compensating for unreliable machine perception without overburdening human operators. His introduction of the Cognitive Cyber-Physical System (C-CPS) framework (2019, 29 citations) further advanced the field by integrating cognitive awareness into cyber-physical manufacturing architectures. Beyond manufacturing, Rahman has explored social robotics, investigating interactions between humanoid robots and virtual humans for real-world tasks. More recently, his research has embraced Industry 5.0 principles, examining cognitive workload, user interface design, and benchmark metrics for HRC performance. With over 240 cumulative citations, his body of work continues to shape how researchers and engineers design safer, more intuitive human-robot systems.

Research Focus

Key Achievements

7
H-Index
10
Papers
242
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Mutual trust-based subtask allocation for human–robot collaboration in flexible lightweight assembly in manufacturing
118 citations · 2018
📈 Most Prolific Year: 2013 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Clemson University, University of West Florida, Montana State University, Vrije Universiteit Brussel, Pennsylvania State University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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