Minli Yang
Papers
2
Total Citations
20
H-Index
2
About
Minli Yang is a robotics researcher specializing in agricultural automation, with a particular focus on navigation and mapping systems for greenhouse environments. Her work addresses critical challenges in deploying autonomous robots in complex agricultural settings, especially where traditional SLAM algorithms falter due to low-density canopy structures. Yang’s most cited paper, “Design and experiments with a SLAM system for low-density canopy environments in greenhouses based on an improved Cartographer framework” (2024, 15 citations), introduces a novel multiline LiDAR-based mapping method that significantly enhances robustness and accuracy for agricultural robots. Building on this, her 2025 study on a fusion positioning navigation system for greenhouse strawberry spraying robots—integrating LiDAR and ultrasonic tags—tackles mapping distortion issues, achieving 5 citations in a short time. Yang’s contributions are pivotal for improving operational efficiency and reducing human labor in precision agriculture. Her innovative fusion of sensor technologies and adaptive SLAM frameworks positions her as a rising figure in agricultural robotics, with work that directly impacts real-world farming productivity and automation reliability.
Research Focus
Key Achievements
Top Papers
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