About

Baoliang Zhao is a prominent researcher specializing in medical robotics, minimally invasive surgery, and human-robot interaction. His work spans several interconnected domains, including continuum surgical robots, sensorless force sensing, robotic ultrasound scanning, and computer-assisted surgical navigation. Zhao's most significant contributions address fundamental challenges in robotic surgery. His development of sensorless force-feedback systems for laparoscopic and minimally invasive procedures tackles the critical problem of haptic loss in robot-assisted surgery, enabling safer tissue interaction without the sterilization complications of traditional sensors. His hybrid adaptive control strategy for continuum robots (60 citations) advances flexible surgical tools suited for natural orifice procedures, while his automated robotic breast ultrasound scanning framework (51 citations) demonstrates innovative path planning for diagnostic imaging applications. Beyond force sensing, Zhao has made notable strides in surgical navigation, developing endoscopic path planning algorithms for nasal surgery and 2D ultrasound–3D CT fusion guidance for percutaneous tumor puncture. His virtual fixture-based human-robot cooperative control further bridges the gap between surgeon autonomy and robotic precision. With over 320 cumulative citations across his published work, Zhao's research has meaningfully shaped the landscape of intelligent surgical robotics, offering practical solutions that enhance safety, accuracy, and clinical usability across diverse surgical specialties.

Research Focus

Key Achievements

14
H-Index
33
Papers
529
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Hybrid Adaptive Control Strategy for Continuum Surgical Robot Under External Load
60 citations · 2021
📈 Most Prolific Year: 2024 (5 Papers)
🤝 Key Collaborators: 78
🏛 Institutions: Chinese Academy of Sciences, University of Nebraska–Lincoln, Shenzhen University, Shenzhen Institutes of Advanced Technology, Chinese University of Hong Kong, Shenzhen

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago