Papers
10
Total Citations
113
H-Index
7
About
Hongbin Lin is a robotics researcher whose work spans surgical robotics, autonomous manipulation, and intelligent robot control systems. His most recognized contribution is the design of a miniaturized tendon-driven articulated surgical drill for minimally invasive spine fusion (2021, 30 citations), which addressed critical limitations in existing steerable drill technologies by offering improved distal dexterity and actuation precision. Complementing this, his 2025 work on surgical embodied intelligence for generalized task autonomy in laparoscopic robot-assisted surgery (24 citations) advances the frontier of adaptable, context-independent surgical automation. Lin has also made foundational contributions to robot introspection and failure recovery, developing wrench-based action grammars (2017, 21 citations) and state-dependent revertive recovery policies (2018, 9 citations) to help robots navigate unexpected disturbances in unstructured environments. His research further extends into vision-based surgical perception, including end-to-end visuomotor learning for needle picking and monocular 3D needle pose estimation — tasks central to autonomous robotic suturing. Through physics-informed deep learning and uncertainty-aware control, Lin consistently bridges theoretical rigor with practical clinical application, positioning himself as a rising contributor to the field of intelligent surgical and autonomous robotics.
Research Focus
Key Achievements
Top Papers
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- 3Online robot introspection via wrench-based action grammars21 citations · 2017
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- 5End-to-End Learning of Deep Visuomotor Policy for Needle Picking8 citations · 2023
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