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About

Linghao Yang is a leading researcher in autonomous driving and robotics, specializing in object-oriented SLAM (Simultaneous Localization and Mapping) and 3D perception. His major contributions center on developing robust quadric landmark representations for dynamic outdoor environments—a critical challenge for real-world autonomous systems. Yang’s pioneering work, "Accurate and Robust Object SLAM With 3D Quadric Landmark Reconstruction in Outdoors" (35 citations), introduced a stereo visual SLAM system integrating deep learning detection with quadric initialization, enabling precise object mapping despite observation noise. He further advanced the field with "Object SLAM With Robust Quadric Initialization and Mapping for Dynamic Outdoors" (12 citations), addressing sensitivity issues in state-of-the-art algorithms. His recent "DynaQuadric" (9 citations) broke new ground by extending quadric SLAM to dynamic scenes, allowing simultaneous tracking of moving objects—a first in the field. Yang also contributed to 3D object detection with "BSH-Det3D" (9 citations), improving LiDAR-based perception in occluded areas using BEV shape heatmaps. With over 65 total citations, Yang’s work is foundational for next-generation autonomous navigation, bridging the gap between static assumptions and real-world dynamic complexity.