Papers
16
Total Citations
264
H-Index
7
About
Dongming Bai is a robotics researcher whose work centers on continuum robots, minimally invasive surgery (MIS) systems, and human-robot interaction. His most significant contributions lie in advancing the design, control, and sensing capabilities of flexible robotic manipulators for use in constrained clinical environments. Bai's highly cited 2018 work on magnetic-based shape estimation for continuum robots (65 citations) established a practical framework for real-time positional feedback, while his 2020 research on SMA-driven variable-stiffness sheaths (57 citations) addressed a fundamental challenge in the field — balancing the competing demands of flexibility and structural rigidity during surgical procedures. His 2019 study on cable-driven continuum robot kinematics and navigation (35 citations) further strengthened the foundation for safe deployment within complex vascular environments. Beyond surgery, Bai has explored wearable human-robot interfaces using surface electromyography, vibrotactile feedback systems for teleoperation, and deep reinforcement learning for autonomous tumor palpation. His diverse portfolio reflects a coherent vision: creating intelligent, perceptive robotic systems that can operate safely and effectively in environments inaccessible to conventional rigid robots, making him a notable contributor to the surgical and medical robotics community.
Research Focus
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