Yongmin Zhong
Monash University, RMIT University, Curtin University, MIT University
Papers
26
Total Citations
401
H-Index
9
About
Yongmin Zhong is a distinguished researcher whose work spans robotics, precision engineering, and surgical systems, with particular expertise in robotic-assisted minimally invasive surgery (RAMIS), haptic feedback, and intelligent path planning. His most cited contribution, a 2009 paper on laser interferometry-based guidance for high-precision robotic positioning (98 citations), established early foundations for his career-long pursuit of precision in robotic systems. Zhong has made significant strides in transforming surgical robotics, developing force-feedback-enabled laparoscopic instruments and teleoperated surgical systems that address a critical gap in current platforms — the absence of haptic sensation. His research on soft tissue characterization, employing Extended Kalman and iterative Kalman filters alongside Hunt-Crossley contact models, has advanced the ability of robotic systems to safely interact with biological tissue, garnering over 75 citations across related works. Complementing this surgical focus, Zhong has pioneered neural network and cellular neural network methodologies for optimal robot path planning, drawing innovative analogies between heat conduction and spatial navigation. Collectively, his body of work reflects a coherent and impactful vision: making robotic systems smarter, safer, and more responsive to the complex demands of real-world clinical and engineering environments.
Research Focus
Key Achievements
Top Papers
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- 7Iterative Kalman filter for biological tissue identification18 citations · 2023
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- 9A new neural network for robot path planning15 citations · 2008
- 10Optimal Robot Path Planning with Cellular Neural Network9 citations · 2011