Papers
15
Total Citations
249
H-Index
7
About
Shabbir Kurbanhusen Mustafa is a robotics researcher whose work sits at the compelling intersection of biologically inspired design, cable-driven mechanisms, and intelligent robot control. His most celebrated contribution is the development of a self-calibrating 7-DOF cable-driven robotic arm that mirrors the architecture of the human arm — incorporating a 3-DOF shoulder, 1-DOF elbow, and 3-DOF wrist — a landmark work that has garnered 93 citations and established him as a leading voice in anthropomimetic robotics. His sustained focus on kinematic design, calibration, and optimization of cable-driven systems has produced highly cited follow-up research, collectively demonstrating that cable-driven architectures can achieve lightweight construction, expansive workspaces, and superior dexterity compared to conventional rigid-link manipulators. Beyond manipulation, Mustafa has extended his expertise to rehabilitation robotics, proposing wearable cable-driven arm rehabilitators designed to assist stroke patients — blending engineering precision with meaningful clinical application. More recently, his research has embraced machine learning, introducing Gaussian process-based approaches to enable robots to adapt intelligently within complex, uncertain environments. With over 230 cumulative citations, Mustafa's career reflects a coherent and impactful vision: making robotic arms more human in form, function, and adaptability.
Research Focus
Key Achievements
Top Papers
- 1Self-Calibration of a Biologically Inspired 7 DOF Cable-Driven Robotic Arm93 citations · 2008
- 2Kinematic design of an anthropomimetic 7-DOF cable-driven robotic arm28 citations · 2010
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- 5Optimal Design of a Bio‐Inspired Anthropocentric Shoulder Rehabilitator18 citations · 2006
- 6Design and motion control of a cable-driven dexterous robotic arm16 citations · 2010
- 7Learning-based robot control with localized sparse online Gaussian process11 citations · 2013
- 8Cable-Driven Robots7 citations · 2014
- 9Learning based robot control with sequential Gaussian process7 citations · 2013
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