About

Shangzhe Sun is a leading researcher at the intersection of robotics, remote sensing, and artificial intelligence, with a primary focus on autonomous navigation, multi-robot collaboration, and infrastructure inspection. His most impactful work, "DCPLD-Net" (32 citations), introduces a diffusion-coupled convolutional neural network for real-time power transmission line detection from UAV-borne LiDAR data, directly addressing critical needs in electric power infrastructure monitoring. Sun's research extends to intelligent multi-robot exploration in challenging non-exposed environments, including underground tunnels and planetary subsurface spaces, where he tackles fundamental challenges in limited perception and GPS-denied navigation. He has developed innovative systems such as the LuoJia-Explorer for collaborative exploration with multimodal LiDAR sensors and the ATCM framework for aerial-terrestrial collaborative SLAM, which enables precise scene reconstruction through heterogeneous robot teams. His practical contributions include the Easy Rocap system, a low-cost motion capture solution for drones that overcomes traditional camera-based limitations. With over 46 total citations across his key publications, Sun's work bridges theoretical advances in multi-robot coordination with real-world applications in disaster response, infrastructure inspection, and space exploration, making him a rising figure in autonomous systems research.

Research Focus

Key Achievements

3
H-Index
5
Papers
46
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
DCPLD-Net: A diffusion coupled convolution neural network for real-time power transmission lines detection from UAV-Borne LiDAR data
32 citations · 2022
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago