Papers
6
Total Citations
52
H-Index
5
About
Yunhui Li is a leading researcher in agricultural robotics and autonomous navigation systems, with a focus on enabling intelligent robots to operate reliably in complex, unstructured environments such as large-scale orchards. His major contributions lie in developing advanced LiDAR-inertial simultaneous localization and mapping (SLAM) systems, including the novel SG-ISBP-SLAM framework that integrates ground optimization and loop closure detection for highly accurate real-time trajectory estimation and map-building. Li has pioneered place recognition techniques using attention score maps for orchard environments, achieving robust localization under challenging conditions where traditional vision systems fail. His work on spatiotemporal calibration algorithms for IMU–LiDAR fusion has significantly improved navigation accuracy by unifying data collection across sensors. With over 50 cumulative citations from his most-cited papers (2021–2025), Li’s research directly addresses critical labor shortages in agriculture by advancing autonomous orchard robots. Notable achievements include his 2023 work on attention-based place recognition, which has become a foundational reference for field robotics, and his 2025 paper on optimal motion planning for nonholonomic agricultural robots operating under multiple constraints. His interdisciplinary approach bridges robotics, sensor fusion, and agricultural engineering.
Research Focus
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Top Papers
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