Papers
23
Total Citations
334
H-Index
13
About
Weibang Bai is a prominent researcher in surgical robotics and autonomous robotic control, whose work has significantly advanced minimally invasive and single-port surgical systems. With a career spanning over half a decade of high-impact publications, Bai has established expertise in tendon-driven flexible robots, macro-micro manipulator systems, and intelligent kinematic modeling for complex surgical platforms. Among his most notable contributions, Bai developed innovative dual-step optimization frameworks for anthropomorphic teleoperation in single-port surgery (33 citations) and pioneered LSTM-based kinematic modeling to address nonlinearities inherent in tendon-driven surgical instruments (26 citations). His work on macro-micro manipulator optimization has improved precision and safety in minimally invasive procedures (29 citations), while his research on backlash compensation and probabilistic neural networks further demonstrates his commitment to bridging the gap between analytical and data-driven robotic modeling. Bai has also contributed to broader robotics challenges, including object grasping using two-stream CNNs (24 citations) and force-feedback robotic spinal drilling systems (22 citations). Collectively accumulating over 230 citations, his body of work reflects a sustained effort to make surgical robotics safer, more precise, and clinically viable — making him an essential reference for researchers and engineers in medical robotics and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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- 6Robotic spinal surgery system with force feedback for teleoperated drilling22 citations · 2019
- 7Model Learning With Backlash Compensation for a Tendon-Driven Surgical Robot20 citations · 2022
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- 10Augmented Neural Network for Full Robot Kinematic Modelling in SE(3)19 citations · 2022