Zhongbo Sun
Papers
38
Total Citations
746
H-Index
16
About
Zhongbo Sun is a robotics and control systems researcher whose work bridges advanced mathematical optimization, neural computation, and rehabilitation engineering. His research spans three deeply interconnected domains: kinematic control of redundant robot manipulators, optimization algorithms for bipedal locomotion, and wearable rehabilitation robotics for upper and lower limb recovery. Among his most influential contributions is his orthogonal projection-based recurrent neural network scheme for repetitive motion generation in redundant manipulators (2020, 121 citations), which resolved a persistent theoretical gap regarding position error fluctuation in kinematic control. His development of sequential quadratic programming and trust region methods for bipedal walking robots and nonlinear model predictive control demonstrates his strength in bringing superlinearly convergent algorithms to real-world robotic systems. Equally notable is his work designing wearable rehabilitation robots—including tension-mechanism upper limb devices and lower limb systems—paired with adaptive iterative learning control and human-in-the-loop paradigms to support stroke patients in practical recovery settings. Sun's noise-tolerant zeroing neurodynamic algorithms further reflect his interest in robust, real-time computation under non-ideal conditions. With over 480 cumulative citations across his top works, his research is making a measurable impact on both theoretical robotics and assistive medical technology.
Research Focus
Key Achievements
Top Papers
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- 4Development and Evaluation of a Wearable Lower Limb Rehabilitation Robot48 citations · 2022
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