Papers
4
Total Citations
33
H-Index
3
About
Yizhe Liu is a robotics researcher specializing in agricultural automation and industrial manipulation, with a focus on visual perception and grasp detection. His work bridges deep learning and robotic systems to enable precise, real-time object recognition and positioning in challenging environments. Liu’s most cited paper, "Recognition and Positioning of Strawberries Based on Improved YOLOv7 and RGB-D Sensing" (2024, 20 citations), introduces a novel approach for detecting elevated-substrate strawberries and their picking points using an enhanced YOLOv7 architecture, significantly improving the speed and accuracy of robotic harvesting. He further advances robotic grasping with "MCT-Grasp" (2024, 7 citations), which integrates multimodal embedding and convolutional modulation transformers to enhance grasp detection accuracy—a critical step toward seamless human-robot interaction. Liu also addresses industrial challenges in "Visual Localization Method for Fastener-Nut Disassembly and Assembly Robot Based on Improved Canny and HOG-SED" (2025, 4 citations), developing robust visual positioning techniques that overcome lighting variations, surface anomalies, and complex backgrounds. With a growing citation impact, Liu’s contributions are shaping the future of intelligent robotics in both agriculture and manufacturing, demonstrating how vision-driven systems can tackle real-world operational constraints.
Research Focus
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