Qiuxia Wu

Xiamen University, South China University of Technology

Papers

Total Citations

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About

Qiuxia Wu is a leading researcher at the intersection of intelligent control systems and autonomous robotics, with a particular focus on bio-inspired neural networks and visual perception for mobile platforms. Her most impactful work, "Self-Organizing Brain Emotional Learning Controller Network for Intelligent Control System of Mobile Robots" (2018), has garnered 51 citations and introduces a groundbreaking adaptive control system that mimics the brain's emotional learning mechanisms. This self-organizing neural network significantly enhances trajectory tracking in mobile robots, offering robust solutions to uncertain disturbances that plague real-world autonomous navigation. More recently, Wu has advanced the field of visual odometry with her 2021 paper "Attention-based Long-term Modeling for Deep Visual Odometry" (6 citations), which addresses the critical challenge of determining camera position from image sequences—a cornerstone technology for AR/VR, autonomous driving, and robotics. By integrating attention mechanisms for long-term temporal modeling, her work overcomes the limitations of conventional hand-crafted feature approaches. Wu’s contributions bridge emotional learning theory and deep learning, positioning her as a key innovator in creating more adaptive, human-like intelligence for autonomous systems.