Yuanfan Xu
Papers
9
Total Citations
221
H-Index
6
About
Yuanfan Xu is a robotics researcher whose work sits at the intersection of multi-robot systems, autonomous exploration, and embedded hardware acceleration. His research has made significant strides in addressing one of mobile robotics' most pressing challenges: enabling teams of robots to collaboratively map and navigate unknown environments under real-world communication constraints. His flagship contribution, SMMR-Explore (2021, 80 citations), introduced a submap-based multi-robot exploration framework using potential field methods without reliance on external positioning, while MR-TopoMap (2022, 55 citations) extended this work by leveraging topological representations to overcome bandwidth bottlenecks. Xu also developed Explore-Bench (2022, 40 citations), a standardized evaluation platform that has become a valuable resource for the autonomous exploration community. Beyond algorithmic contributions, his work on communication-efficient mapping through Gaussian Mixture Models and CNN accelerator architectures like INCA and INCAME demonstrates a distinctive commitment to bridging intelligent algorithms with practical embedded hardware deployment. Collectively accumulating over 220 citations, Xu's research consistently targets the gap between theoretical multi-robot coordination and real-world computational and communication limitations, making him a notable voice in field robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 5INCA: INterruptible CNN Accelerator for Multi-tasking in Embedded Robots9 citations · 2020
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- 7INCAME: Interruptible CNN Accelerator for Multirobot Exploration5 citations · 2021
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