Wendong Niu

Shanxi Agricultural University, Tianjin University

Papers

Total Citations

H-Index

About

Wendong Niu is a researcher whose work bridges agricultural robotics, intelligent control systems, and multi-agent coordination. His most cited paper, “YOLOv8-ECFS: A lightweight model for weed species detection in soybean fields” (2024), has already garnered 29 citations, reflecting its practical impact on precision agriculture. This contribution addresses the critical need for efficient, real-time weed detection in crop management, offering a lightweight deep-learning solution that balances accuracy with computational efficiency. Niu also explores advanced control theory, as seen in his work on Koopman operator-based data-driven online learning control for omni-directional mobile manipulators (2025). This research tackles the challenge of modeling complex, nonlinear, and strongly coupled robotic systems without requiring mechanistic models, using fully data-driven approaches to enable adaptive, real-time control. Additionally, his study on multi-underwater glider formation using virtual hinges (2023) demonstrates his versatility in distributed robotics and swarm coordination. Together, Niu’s work spans from field-level agricultural AI to sophisticated robotic manipulation and underwater swarm dynamics, showcasing a commitment to solving real-world problems through innovative, data-driven methodologies.