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About

Zihao Pan is a researcher advancing the frontiers of robotic perception and autonomous navigation, with a primary focus on simultaneous localization and mapping (SLAM) and 3D reconstruction. His most influential work, "Optimization RGB-D 3-D Reconstruction Algorithm Based on Dynamic SLAM" (2023, 36 citations), tackles the critical challenge of robust mapping in dynamic environments by integrating a dynamic feature segmentation framework with RGB-D sensors, enabling intelligent robots to maintain accurate spatial awareness amidst moving objects. Pan has also pioneered the use of ground texture for camera pose estimation and relocalization, as demonstrated in his 2024 paper (9 citations), which leverages underutilized ground information to enhance system robustness against environmental changes. His contributions extend to high-precision offline mapping systems using binary descriptors (2023, 7 citations) and real-time 3D reconstruction through improved AKAZE features and multi-layer detection networks (2024, 5 citations). Collectively, Pan’s work addresses fundamental limitations in SLAM—dynamic interference, environmental variability, and computational efficiency—with over 57 total citations, establishing him as a rising voice in making autonomous systems more reliable and perceptually aware for real-world deployment.