Qiyi Tong

Italian Institute of Technology, Zhejiang University of Technology

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About

Qiyi Tong is a researcher specializing in visual Simultaneous Localization and Mapping (vSLAM), semantic scene understanding, and robotics perception. Their work sits at the intersection of computer vision and autonomous systems, with a particular focus on advancing SLAM technologies to handle the complexities of dynamic and unstructured environments. Tong's most influential contributions include comprehensive survey work on Semantic Visual SLAM, which has collectively accumulated nearly 30 citations and has become a key reference for researchers navigating this rapidly evolving field. These surveys systematically examine how semantic information can be integrated into traditional vSLAM pipelines to improve robustness in challenging real-world conditions — a critical challenge for autonomous vehicles and robotic navigation. Beyond survey contributions, Tong has pursued innovative system-level research, notably developing TXSLAM, a monocular SLAM system that uniquely leverages planar text features for tighter semantic coupling, enabling more accurate camera pose estimation. Their work on humanoid robot perception further demonstrates a commitment to bridging high-level semantic understanding with practical robotic applications. Collectively, Tong's research reflects a consistent drive to push vSLAM beyond controlled environments toward reliable deployment in complex, dynamic settings.