Papers

3

Total Citations

46

H-Index

3

About

Chao Ban is a researcher specializing in agricultural robotics and multi-sensor fusion for autonomous navigation in complex field environments. His work centers on developing robust localization and navigation systems that integrate cameras, LiDAR, IMU, and GNSS sensors to enable robots to operate reliably in unstructured agricultural settings. Ban’s major contributions include pioneering a real-time Camera-LiDAR-IMU fusion method for extracting navigation lines between maize field rows, which achieved 29 citations since 2024, and a subsequent fusion approach for navigation line extraction under dense corn canopy, garnering 12 citations in 2025. His notable work on a smooth and accurate LiDAR-GNSS-IMU localization method with confidence estimation (5 citations) provides a versatile framework for state estimation in both indoor and outdoor environments, addressing the challenge of maintaining accuracy across varied conditions. By leveraging the complementary strengths of multiple sensors, Ban’s research directly advances the practicality of autonomous agricultural machinery, offering solutions for precise row following and robust localization in challenging crop canopies. His work is highly relevant for researchers and engineers developing field robots for precision agriculture.

Research Focus

Key Achievements

3
H-Index
3
Papers
46
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
A Camera-LiDAR-IMU fusion method for real-time extraction of navigation line between maize field rows
29 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: China Agricultural University, Beijing Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago