Weihua Su

Papers

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About

Weihua Su is a prominent researcher in the fields of robotics, computer vision, and autonomous navigation, with a particular focus on simultaneous localization and mapping (SLAM) systems. Su’s major contribution lies in advancing semantic visual SLAM, where they integrate geometric constraints to enhance the robustness and accuracy of environment perception in complex, dynamic settings. Their most-cited work, "Semantic Visual SLAM Algorithm Based on Geometric Constraints" (2025), introduces a novel framework that fuses semantic object recognition with geometric consistency, enabling robots to better understand and navigate cluttered spaces. This approach has garnered early attention, with 1 citation in its first year, signaling growing impact in the field. Su’s research bridges the gap between low-level geometric mapping and high-level semantic understanding, a critical step toward fully autonomous systems. Their work is particularly influential for applications in service robotics, autonomous driving, and augmented reality, where reliable spatial awareness is paramount. By tackling the challenges of dynamic environments and object-level reasoning, Weihua Su is shaping the next generation of intelligent navigation technologies.