Chenglu Wen

China Agricultural University, Xiamen University

Papers

10

Total Citations

231

H-Index

6

About

Chenglu Wen is a researcher whose work spans computer vision, robotics, and 3D spatial intelligence, with particular expertise in LiDAR-based localization, scene reconstruction, and human-centered sensing systems. Beginning with early contributions in biological imaging — including insect classification systems (115 citations) and microorganism tracking — Wen's research trajectory has evolved toward sophisticated 3D understanding of real-world environments. His most impactful recent work centers on LiDAR localization for autonomous vehicles and robotics, producing a series of influential methods including STCLoc, LiSA, and LightLoc, which address critical challenges such as spatio-temporal pose estimation, semantic scene awareness, and dramatically accelerated training pipelines. His HSC4D project (2022) stands out as a particularly innovative contribution, enabling human-centered 4D scene capture across large-scale indoor-outdoor environments using only wearable IMUs and LiDAR — a space-free approach with broad implications for digital twin creation and human-robot interaction. With cooperative indoor 3D mapping and geometric motion estimation rounding out his portfolio, Wen's cumulative citation record reflects a researcher steadily building foundational tools for the next generation of intelligent, spatially aware autonomous systems.

Research Focus

Key Achievements

6
H-Index
10
Papers
231
Total Citations
23
Avg Citations/Paper
🏆 Most Cited Paper
Local feature-based identification and classification for orchard insects
115 citations · 2009
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 35
🏛 Institutions: China Agricultural University, Xiamen University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago