Xiufeng Dai

Papers

Total Citations

H-Index

About

Xiufeng Dai is a leading researcher in agricultural robotics and multi-sensor fusion, with a focus on enabling autonomous navigation in challenging environments. His most-cited work, "Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR" (2022), addresses a critical bottleneck in precision agriculture: the unreliability of conventional LIDAR-based positioning on uneven, slippery greenhouse floors. By fusing Ultra-Wideband (UWB), inertial measurement units (IMU), odometry (ODOM), and LIDAR data, Dai developed a robust positioning system that mitigates cumulative odometry errors from wheel slip—a common problem in soil-based or wet greenhouse conditions. This contribution has garnered 42 citations, reflecting its practical impact on greenhouse automation. Beyond this work, Dai’s research spans sensor integration, robot localization, and adaptive control for agricultural settings, bridging the gap between industrial robotics and the unstructured, dynamic environments of modern farming. His achievements include advancing the reliability of autonomous ground robots in precision agriculture, a field where even small positioning errors can disrupt tasks like harvesting or spraying. For students and researchers, Dai’s work exemplifies how thoughtful sensor fusion can solve real-world operational challenges, making him a key figure in the evolution of smart farming technologies.