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About

Ling Pei is a prominent researcher specializing in visual simultaneous localization and mapping (SLAM), autonomous navigation, and sensor fusion for robotics and intelligent systems. His most significant contribution is the development of TextSLAM, a groundbreaking visual SLAM framework that integrates detected text objects as semantic planar features, enriching traditional SLAM pipelines with both geometric and linguistic information. First introduced in 2020 and substantially extended in 2023, TextSLAM has collectively garnered over 80 citations, establishing Pei as a leading voice in semantically-aware localization. Beyond text-based SLAM, his research spans visual place recognition using structural line features in Manhattan World environments, 360° camera-based visual-inertial odometry, LiDAR-inertial odometry with uncertainty awareness, and even neural radiance field reconstruction from infrared imagery through Thermal-NeRF. Pei has also made practical contributions to industrial robotics, developing intelligent inspection systems for electrical substations that incorporate pose relocalization and concept-learning-based object recognition. His work consistently bridges theoretical innovation with real-world deployment, making him a versatile and impactful figure across mobile robotics, autonomous driving, and industrial automation research communities.