Xiangru Yan
Papers
2
Total Citations
26
H-Index
2
About
Xiangru Yan is a rising researcher at the forefront of intelligent robotics and neural computation, with key contributions in image fusion, visual servo control, and medical robotics. Yan’s most cited work introduces a groundbreaking **variable-gain fixed-time convergent and robust zeroing neural network (VFCR-ZNN)** for image fusion, achieving superior noise reduction and convergence speed—a critical advance for real-time imaging systems. This 2024 paper has already garnered **24 citations**, reflecting its immediate impact on robust neural network design. In 2025, Yan pioneered an **uncalibrated model-free visual servo control method** for robotic endoscopic surgery, integrating neural networks to eliminate reliance on precise kinematic models and camera calibration—a major leap toward generalizable, autonomous surgical assistance. This work, though recent, addresses a long-standing barrier in minimally invasive robotics. Yan’s research uniquely bridges theoretical neural dynamics and practical robotic systems, offering scalable solutions for noisy environments and constrained surgical settings. As a young innovator, Yan’s trajectory promises to reshape how robots perceive and act in complex, unstructured environments, with implications for medical robotics, autonomous systems, and beyond.
Research Focus
Key Achievements
Top Papers
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- 2