Jinzhuang Xiao
Papers
8
Total Citations
33
H-Index
4
About
Dr. Jinzhuang Xiao is a leading researcher in intelligent robotic control systems, with a career spanning over two decades of innovation in human-robot interaction and fault-tolerant robotics. His work centers on three key areas: gesture recognition for seamless human-robot communication, adaptive control under actuator constraints, and advanced path planning for autonomous vehicles. Dr. Xiao’s most impactful contribution is his 2019 paper on an improved Faster R-CNN algorithm for gesture recognition, which has garnered 8 citations and represents a pioneering application of deep learning to enhance robot responsiveness to human cues. In his foundational 2006 work on passive fault-tolerant control using fuzzy rules (7 citations), he developed novel strategies to maintain robotic performance despite actuator saturation, introducing local high-gain feedback techniques that have influenced subsequent research. His 2006 adaptive control paper (6 citations) further advanced this field by integrating filter functions with gravity compensation. Dr. Xiao has also explored generalized dynamic fuzzy neural networks for tracking control and, most recently, a multi-strategy improved sparrow search algorithm for indoor AGV path planning (2024). His sustained focus on practical, robust solutions—from fuzzy sliding mode controllers to impact-free force-position control—demonstrates a career dedicated to making robots more reliable, intuitive, and capable in real-world applications.
Research Focus
Key Achievements
Top Papers
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- 6Robot force position control without impact: Method and application2 citations · 2010
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