He Guo

University of Science and Technology of China, Zhengzhou University of Science and Technology

Papers

Total Citations

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About

He Guo is a robotics researcher whose work focuses on enabling autonomous systems to perceive and navigate complex, dynamic environments. His primary research areas include Simultaneous Localization and Mapping (SLAM), 3D point cloud processing, and computer vision for mobile robotics. Guo’s most cited paper, "Semantic Lidar Odometry and Mapping for Mobile Robots Using RangeNet++" (2022, 4 citations), addresses a critical limitation in existing SLAM systems: their reliance on static assumptions. By integrating semantic segmentation, his work allows robots to filter out dynamic objects—such as moving vehicles or pedestrians—during point cloud registration, dramatically improving localization accuracy in highly dynamic real-world settings. This contribution is foundational for deploying autonomous robots in busy urban or industrial environments. More recently, in "Multi-object road waste detection and classification based on binocular vision" (2024, 2 citations), Guo tackles the challenge of efficient object detection for intelligent road cleaning robots, proposing a system that avoids processing entire image regions unnecessarily. His work bridges the gap between robust environmental mapping and practical, task-specific perception, making him a notable emerging voice in field robotics and autonomous navigation.