Papers
2
Total Citations
13
H-Index
2
About
Yilu Xu is a researcher at the intersection of rehabilitation robotics and precision agriculture, with key contributions in intelligent motion planning and machine vision. Their most cited work introduces a **multistrategy improved whale optimization algorithm (MWOA)** for trajectory planning in upper extremity exoskeleton rehabilitation robots, addressing the critical need for safe, effective, and personalized patient therapy. This paper has garnered **11 citations**, reflecting its impact on advancing robotic rehabilitation. In a parallel line of inquiry, Xu developed **AC R-CNN**, a pixelwise instance segmentation model specifically designed to analyze the cap traits of *Agrocybe cylindracea* mushrooms. This work, with **2 citations**, demonstrates a novel application of deep learning to smart agriculture, enabling high-throughput phenotyping in greenhouse environments. By bridging robotics and agricultural AI, Xu’s research showcases a versatile approach to solving real-world problems—from improving patient recovery outcomes to enhancing crop quality assessment. Their work is notable for adapting optimization and computer vision techniques to domain-specific challenges, offering valuable insights for students and researchers in mechatronics, bio-inspired algorithms, and precision farming.
Research Focus
Key Achievements
Top Papers
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- 2