Shiqiang Yang

Xi'an University of Technology, Tsinghua University

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About

Shiqiang Yang is a researcher whose work spans robotics, computer vision, and intelligent systems, with a particular focus on autonomous navigation and human-computer interaction. His most recognized contribution, "Research on Application of Genetic Algorithm for Intelligent Mobile Robot Navigation Based on Dynamic Approach" (2007, 6 citations), introduces an innovative navigation model that elegantly combines target-seeking and obstacle-avoidance behaviors through nonlinear differential equations grounded in dynamical systems stability theory — a foundational approach for intelligent mobile robotics. His earlier work on integrating omni-directional imagery with adaptive neural networks for outdoor road scene understanding demonstrated an early commitment to robust, real-world robotic perception. More recently, Yang has extended his expertise into action recognition, contributing the NST-GCN framework for hand gesture and action recognition, leveraging skeleton-based graph convolutional networks to overcome challenges posed by complex backgrounds and variable movement speeds — with clear applications in intelligent surveillance and human-robot interaction. Across his career, Yang's research reflects a consistent vision: building intelligent systems that perceive, reason, and act within dynamic real-world environments, bridging classical control theory with modern deep learning approaches.