About

Abdullah Aamir Hayat is a robotics researcher whose work spans two deeply interconnected domains: robotic kinematics and self-reconfigurable robotic systems. His early contributions focused on the kinematic identification of industrial robots, most notably through systematic methods for determining Denavit-Hartenberg parameters — foundational work that has garnered over 60 citations and addressed real-world inaccuracies between manufacturer-specified and actual robot configurations. He further advanced this field by developing geometric approaches using monocular cameras for kinematic calibration, cited nearly 70 times. Hayat's research subsequently expanded into self-reconfigurable and adaptive robotics, where he has made particularly distinctive contributions. His 2020 taxonomy and evaluation framework (TAEV) for self-reconfigurable robots, his most-cited work with 84 citations, brought much-needed systematic structure to a fragmented field. His Panthera robot series — reconfigurable pavement-sweeping platforms capable of adapting their width to different environments — exemplifies his translational approach, blending mechanical design, vision-based control, and deep learning for real-world inspection and cleaning tasks. Collectively, his papers have accumulated over 480 citations, reflecting sustained influence across academic and applied robotics communities. Hayat's portfolio represents a coherent research vision: building robots that are not only precise, but intelligently adaptable to dynamic physical environments.

Research Focus

Key Achievements

14
H-Index
43
Papers
735
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
A Framework for Taxonomy and Evaluation of Self-Reconfigurable Robotic Systems
84 citations · 2020
📈 Most Prolific Year: 2022 (11 Papers)
🤝 Key Collaborators: 67
🏛 Institutions: Singapore University of Technology and Design, Indian Institute of Technology Delhi, Delhi Technological University, United Arab Emirates University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago