Wei‐Wei Gao

Shanghai University of Engineering Science

Papers

Total Citations

H-Index

About

Wei-Wei Gao is a leading researcher in mobile robotics and autonomous navigation, with a primary focus on advancing visual-inertial SLAM (Simultaneous Localization and Mapping) technologies. Gao’s most impactful work tackles a critical challenge in robotics: maintaining accurate localization in low-light and weak-texture environments, where traditional visual SLAM methods often fail. Their landmark 2024 study introduced an innovative point-line feature visual-inertial SLAM algorithm that significantly improves tracking robustness and localization precision under these adverse conditions. By integrating both point and line features into the VINS-mono framework, Gao’s approach reduces tracking failures and enhances system reliability, achieving a 40% improvement in localization accuracy over conventional methods. This work has already garnered 4 citations, demonstrating its immediate relevance to the field. Gao’s contributions are particularly valuable for applications in search-and-rescue, underground exploration, and autonomous driving, where environmental challenges are common. Their research bridges the gap between theoretical SLAM advancements and practical, real-world deployment, making them a key figure in the next generation of robust, perception-driven robotic systems.