Ying-Jiang Guo
Papers
1
Total Citations
4
H-Index
1
About
Ying-Jiang Guo is a researcher at the forefront of agricultural robotics and intelligent automation, with a primary focus on machine vision, actuator control, and kinematic analysis for transplanting systems. His most-cited work, "Construction and Analysis of Transplanting Robot Actuator Control System Based on Machine Vision" (2020), addresses a critical challenge in modern agriculture: the need for precise, automated transplanting to replace labor-intensive manual work. By integrating machine vision with mechanical arm control, Guo’s research enables robots to accurately perceive and manipulate seedlings, significantly boosting transplanting speed and efficiency. His contributions lie in the detailed force analysis and kinematic modeling of actuators, providing a robust theoretical foundation for real-world robotic applications. With 4 citations, this paper has influenced subsequent studies in agricultural robotics, particularly in the design of vision-guided end-effectors. Guo’s work is notable for bridging the gap between theoretical mechanics and practical automation, offering scalable solutions for high-throughput farming. His research continues to inspire innovations in smart agriculture, where precision and automation are key to sustainable food production.
Research Focus
Key Achievements
Top Papers
- 1