Xuedong Wang
Papers
1
Total Citations
24
H-Index
1
About
Xuedong Wang is a leading researcher in multi-robot systems, with a primary focus on cooperative localization and fault-tolerant robotics. His most influential work tackles the critical challenge of multi-robot cooperative localization (CL) in the presence of spurious sensor data—a problem that can cause catastrophic state estimation failures in robot teams. In his highly cited 2021 paper, Wang introduced a fully decentralized CL algorithm based on covariance union, a mathematically rigorous approach that ensures consistent state estimates even when robots encounter faulty or malicious sensor readings. This work, which has accumulated 24 citations, represents a significant advance in making multi-robot systems robust to real-world sensor failures. Wang’s contributions are particularly valuable for applications in search-and-rescue, autonomous exploration, and industrial automation, where reliable team coordination is essential. By addressing the fundamental tension between decentralization and fault tolerance, his research provides a practical framework for deploying resilient robot teams in uncertain environments.
Research Focus
Key Achievements
Top Papers
- 1