Shunfan Di

Papers

Total Citations

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About

Shunfan Di is a robotics researcher whose work focuses on advancing autonomous navigation in complex, dynamic environments. His primary research areas include LiDAR-based Simultaneous Localization and Mapping (SLAM), 3D point cloud processing, and real-time robot perception. Di’s most cited work, “A LiDAR Mapping System for Robot Navigation in Dynamic Environments” (2023, 20 citations), addresses a critical bottleneck in field robotics: while multi-line LiDAR enables accurate real-time positioning and environmental mapping, the resulting 3D point cloud maps are often too dense or unstructured for direct use in navigation. His contribution lies in bridging this gap, developing mapping pipelines that transform raw sensor data into navigation-ready representations, even in settings with moving objects. This work has practical implications for autonomous vehicles, warehouse robots, and search-and-rescue systems. Though early in his career, Di’s research demonstrates a clear focus on translating theoretical SLAM advances into deployable solutions, making him a promising voice in the robotics community. His citation count—modest but growing—reflects the emerging relevance of his approach to real-world autonomy challenges.