Merve Bazman
Papers
5
Total Citations
53
H-Index
4
About
Merve Bazman is a leading researcher in the field of robotic-assisted minimally invasive surgery (MIS), with a focus on the design, control, and force-sensing capabilities of dexterous surgical instruments. Her work centers on developing novel parallel robotic forceps wrists that offer exceptional dexterity, including a 4DOF articulated forceps with a large orientation workspace (±90° pitch/yaw, 360° roll) and a back-drivable 3DOF wrist mechanism. A key contribution is her pioneering work in sensorless force/torque estimation, where she combines reaction force observers with neural networks to accurately estimate tip forces on rigid-link parallel wrists—a critical advancement for haptic feedback in telesurgery. She has also developed hybrid sensing methods for 6-axis tip force estimation on hyper-redundant (11-DOF) surgical robots and designed a modular, redundant laparoscopic system integrating a 7DOF industrial robot for remote center of motion. With multiple papers each garnering over a dozen citations, Bazman’s research directly addresses the core challenges of surgical robotics: achieving high dexterity, backdrivability, and accurate force sensing without bulky external sensors. Her work is essential reading for anyone interested in the next generation of intelligent, minimally invasive surgical tools.
Research Focus
Key Achievements
Top Papers
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