Ruihan Xu

University of Michigan–Ann Arbor

Papers

3

Total Citations

9

H-Index

2

About

Ruihan Xu is a robotics researcher whose work lies at the intersection of semantic mapping, multi-robot coordination, and probabilistic AI. Their major contributions include pioneering open-vocabulary mapping with quantifiable uncertainty through the development of LatentBKI, a novel algorithm that integrates vision-language models into continuous mapping frameworks—enabling robots to reason about arbitrary semantic categories rather than being limited to a fixed set. This work, published in 2025, has already garnered 3 citations for its foundational approach to open-dictionary robotic perception. Xu also advanced decentralized multi-robot planning with Stein Variational Belief Propagation (2024, 2 citations), a method that addresses high-dimensional coordination challenges under uncertainty and obstacle constraints. Earlier in their career, Xu participated in the ImageCLEF 2013 Robot Vision Challenge as part of the MIAR ICT team, contributing to indoor scene classification and object recognition. With a growing citation footprint and a focus on bridging language, perception, and uncertainty-aware robotics, Xu is shaping the next generation of intelligent, collaborative robotic systems.

Research Focus

Key Achievements

2
H-Index
3
Papers
9
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
MIAR ICT participation at Robot Vision 2013
4 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: University of Michigan–Ann Arbor

Top Papers

  1. 1
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  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago