Xiaoling Lv

Hebei University of Technology

Papers

9

Total Citations

158

H-Index

5

About

Xiaoling Lv’s research sits at the intersection of intelligent robotics, computer vision, and human-robot interaction, with a strong emphasis on enabling robots to perceive and act in complex, real-world environments. Her most impactful work, “Improved YOLOv4-tiny network for real-time electronic component detection” (61 citations), addresses a critical industrial need: rapid, accurate visual recognition of small, moving objects on conveyor belts for robotic grasping. This contribution to lightweight deep learning for manufacturing has significant practical value. Complementing this, her early foundational paper “Robot control based on voice command” (60 citations) demonstrated a pioneering, natural-language interface for mobile robots, showcasing the feasibility of speech-driven control. Lv’s broader portfolio explores multi-modal perception, including low-illumination image enhancement for space environments (DC-WGAN algorithm) and sound source localization using robot hearing and vision—work that integrates auditory and visual cues for robust tracking and teleoperation. Her research consistently tackles real-world constraints, from factory floors to space stations, making her a notable figure in applied robotics. With over 150 total citations, Lv’s work has shaped both industrial automation and service robotics, offering practical solutions for robots that must see, hear, and respond intelligently.

Research Focus

Key Achievements

5
H-Index
9
Papers
158
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Improved YOLOv4-tiny network for real-time electronic component detection
61 citations · 2021
📈 Most Prolific Year: 2008 (5 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Hebei University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago