Papers

3

Total Citations

14

H-Index

3

About

Qiuyi Gu is a robotics researcher whose work advances collaborative perception and mapping for multi-robot systems operating in unknown, communication-constrained environments. Their research centers on three key areas: open-vocabulary scene understanding, radio-frequency mapping, and decentralized exploration. Gu’s most impactful contribution is MR-COGraphs (2025, 7 citations), a communication-efficient system that enables multiple robots to build 3D scene graphs with open-vocabulary labels using foundation models—allowing robots to understand not just geometry, but semantic meaning in unfamiliar spaces. In MD-RadioMap (2023, 4 citations), Gu pioneered multi-drone radio map construction using single-anchor ultra-wideband localization, critical for logistics drones that depend on reliable cellular and GPS signals. Earlier work, MR-GMMExplore (2022, 3 citations), introduced a Gaussian Mixture Model approach for multi-robot exploration without external positioning, solving the challenge of relative pose estimation under limited bandwidth. Collectively, Gu’s research addresses the fundamental tension between rich environmental understanding and the harsh realities of real-world communication constraints, making their work highly relevant for autonomous search-and-rescue, warehouse logistics, and planetary exploration.

Research Focus

Key Achievements

3
H-Index
3
Papers
14
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
MR-COGraphs: Communication-Efficient Multi-Robot Open-Vocabulary Mapping System via 3D Scene Graphs
7 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University Town of Shenzhen, Tsinghua University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago