Papers

1

Total Citations

16

H-Index

1

About

Dr. Xiao Bai is a leading researcher in agricultural robotics and intelligent vision systems, with a particular focus on autonomous navigation for harvesting machinery. His most impactful work addresses a critical challenge in precision agriculture: improving the accuracy and robustness of visual navigation under complex field conditions. In his highly cited 2020 study, Dr. Bai proposed an improved random sampling consensus (RANSAC) algorithm specifically designed for vision-based path detection in intelligent harvester robots. This algorithm significantly enhances the detection of navigation lines by filtering out interference from uneven terrain, varying lighting, and crop debris—common obstacles that degrade conventional computer vision performance. The work has garnered 16 citations, reflecting its practical value for developing more reliable autonomous agricultural equipment. Dr. Bai’s contributions sit at the intersection of robotics, computer vision, and agricultural engineering, helping to bridge the gap between theoretical algorithms and real-world deployment. His research is essential reading for engineers and scientists working on field robot autonomy, sensor fusion, and robust perception systems for unstructured environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
16
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Improved random sampling consensus algorithm for vision navigation of intelligent harvester robot
16 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Engineering School of Information and Digital Technologies

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago