Papers
16
Total Citations
206
H-Index
8
About
A. H. Abdul Hafez is a prominent robotics researcher whose work spans visual servoing, space robotics, robot manipulation, and autonomous navigation. He is perhaps best known for his pioneering contributions to hybrid visual servoing, where he developed novel algorithms that intelligently combine image-based (IBVS) and position-based (PBVS) visual servoing to overcome the limitations of each approach individually. His 2007 paper on optimizing a 2D/3D hybrid objective function and its 2008 successor leveraging online boosting techniques have together garnered nearly 60 citations, establishing him as a key figure in robot vision control research. Abdul Hafez has also made significant strides in space robotics, particularly in reactionless visual servoing for dual-arm and multi-arm space robots — work that addresses the critical challenge of controlling robotic manipulators aboard satellites without disturbing the base spacecraft's orientation. His research further extends to intelligent manipulation in cluttered environments, where he applied machine learning to predict support ordering among objects, accumulating over 47 citations across two related studies. Complementing these contributions, his work on path planning using convex optimization and feature-based localization in crowded urban environments reflects a broad, impact-driven research vision bridging robot perception, learning, and control.
Research Focus
Key Achievements
Top Papers
- 1Visual Servoing by Optimization of a 2D/3D Hybrid Objective Function31 citations · 2007
- 2Hybrid Visual Servoing by Boosting IBVS and PBVS28 citations · 2008
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- 4Learning support order for manipulation in clutter24 citations · 2013
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- 6Reactionless visual servoing of a dual-arm space robot20 citations · 2014
- 7PATH PLANNING FOR VISUAL SERVOING AND NAVIGATION USING CONVEX OPTIMIZATION10 citations · 2015
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