Papers

5

Total Citations

92

H-Index

4

About

Yiliang Xu’s research lies at the intersection of multi-robot systems, autonomous navigation, and sensor-based perception, with a focus on solving real-world challenges in dynamic, unstructured environments. His most influential work addresses the problem of cooperative search for multiple unknown transient radio sources using paired mobile robots—a scenario where signals are anonymous, short-lived, and unpredictable. In his 2014 paper (53 citations), Xu developed a localization method that enables robot teams to collaboratively track these elusive sources despite limited sensing ranges and intermittent transmissions, laying critical groundwork for applications in disaster response and wildlife monitoring. He also contributed to automatic building exterior mapping (11 citations) using multilayer feature graphs, aiding energy retrofitting by helping robots identify facades during simultaneous localization and mapping. More recently, Xu explored visual programming for robot navigation, allowing users to specify tasks using high-level landmarks in a virtual reality environment built from vSLAM data. His work consistently bridges theory and practice, advancing how robots perceive, coordinate, and act in complex, real-world settings.

Research Focus

Key Achievements

4
H-Index
5
Papers
92
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Cooperative Search of Multiple Unknown Transient Radio Sources Using Multiple Paired Mobile Robots
53 citations · 2014
📈 Most Prolific Year: 2014 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Kitware (United States), Texas A&M University, Apple (United States), Mitchell Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago