Yinghu Cai
Papers
3
Total Citations
26
H-Index
2
About
Yinghu Cai is a robotics and agricultural automation researcher whose work focuses on intelligent navigation and perception systems for field robots, particularly in challenging paddy field environments. His major contributions lie in developing integrated navigation solutions that combine sensor fusion, vision-based trajectory generation, and robust crop row detection to enable autonomous maneuvering in unstructured agricultural settings. His most cited paper, "Design and experiment of an integrated navigation system for a paddy field scouting robot" (2023, 14 citations), demonstrates practical deployment of multi-sensor systems for precision agriculture. Cai further advanced field robotics with "Vision-based trajectory generation and tracking algorithm for maneuvering of a paddy field robot" (2024, 10 citations), which addresses real-time path planning under dynamic field conditions. His latest work, "PRSGNet: A robust framework for crop row detection in complex field scenarios" (2025, 2 citations), introduces a deep learning approach to overcome visual challenges like varying lighting and plant occlusion. With cumulative citations reflecting growing interest in agricultural robotics, Cai’s research bridges the gap between theoretical control algorithms and real-world field deployment, offering scalable solutions for autonomous crop monitoring and management.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3