Yuhang He

Institute of Geodesy and Geophysics, Tianjin University of Technology, Sun Yat-sen University

Papers

Total Citations

115

H-Index

About

Yuhang He is a leading researcher at the intersection of autonomous driving, robotics, and artificial intelligence perception. His work focuses on transforming raw sensor data into actionable intelligence for self-driving systems, with major contributions in LiDAR-camera fusion and multimodal perception. He pioneered a parameter self-adaptive framework that converts 3-D LiDAR point clouds into 2-D dense depth maps, a breakthrough that bridges the gap between laser scanners and CCD cameras for enhanced environmental perception in autonomous vehicles (59 citations). His influential 2024 paper on AI-driven perception fusion, with 31 citations, establishes perception as the critical information input module that determines the lower limit of autonomous driving system performance. He has also advanced human-robot interaction by developing LSTM-based natural language description systems for car images, enabling robots to verbally describe visual scenes (25 citations). He’s notable for his systematic approach to digital perception, continuously pushing autonomous systems closer to understanding the real physical world. His work is essential reading for students and researchers in autonomous driving, robotics, and sensor fusion, offering foundational insights into how machines perceive and interpret their surroundings.