Tingwu Yan
Papers
2
Total Citations
9
H-Index
2
About
Tingwu Yan is a researcher specializing in robotics and autonomous systems, with a particular focus on perception, calibration, and environmental mapping for agricultural and mobile robots. His work addresses critical challenges in robotic manipulation and navigation, notably through his research on hand–eye calibration accuracy for apple-picking robots. In his most-cited paper (2023, 6 citations), Yan developed a method based on the Iterative Closest Point algorithm to improve the precision of hand–eye coordination, directly enhancing the efficiency and accuracy of fruit-harvesting robots. Additionally, his 2022 work on adaptive threshold line segment feature extraction for laser radar scanning environments (3 citations) advances the creation of accurate maps for autonomous mobile robot navigation, tackling issues of sensor noise and sparse data. Though early in his career, Yan’s contributions are already demonstrating practical impact in precision agriculture and robotics. His research bridges theoretical calibration techniques with real-world applications, offering valuable insights for students and engineers working on robotic perception, sensor fusion, and autonomous navigation in unstructured environments.
Research Focus
Key Achievements
Top Papers
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- 2