Xinghua Zhang
Papers
4
Total Citations
34
H-Index
3
About
Xinghua Zhang is a researcher whose work spans robotics, control systems, and probabilistic estimation, with contributions that bridge theoretical rigor and practical engineering applications. Zhang's most influential work includes an improved Rao-Blackwellised particle filter enhanced through randomly weighted particle swarm optimization, which has garnered 16 citations and addresses key challenges in state estimation for complex dynamic systems. In the domain of robotics and control, Zhang has made notable strides in developing decentralized robust tracking control strategies for 2-degree-of-freedom planar robot manipulators, tackling the persistent challenges of disturbances and uncertainties by decomposing the system into individual joints with carefully designed controllers — work recognized across multiple publications. More recently, Zhang has expanded into soft robotics, proposing a gesture-adaptive soft-rigid robotic hand featuring pneumatic two-segment fingers designed to enhance grasping versatility and compliance, a study that has already attracted 8 citations since 2022. Collectively, Zhang's portfolio reflects a coherent research vision centered on advancing intelligent, robust, and adaptive robotic systems, making meaningful contributions to both foundational control theory and next-generation robotic hardware design.
Research Focus
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Top Papers
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