Papers
3
Total Citations
28
H-Index
3
About
Mei Wu is a leading researcher in multirobot systems, with a primary focus on decentralized cooperative localization, simultaneous localization and mapping (SLAM), and fault-tolerant robot navigation. Her work addresses critical challenges in enabling robot teams to operate reliably in real-world environments. Wu’s most influential contribution is her 2018 paper on decentralized cooperative localization with fault detection and isolation, which has garnered 13 citations and provides a robust framework for estimating robot positions while identifying and mitigating sensor or communication failures—a key step toward resilient multirobot teams. Her 2014 study on distributed SLAM using an improved particle filter, with 11 citations, demonstrated that distributed systems can match the estimation accuracy of centralized approaches while requiring only one-fifth of the computation time, a breakthrough for scalable robotics. Wu also advanced practical SLAM implementations by integrating particle filters with RPLidar sensors for landmark-based mapping. Her research bridges theoretical algorithms and real-world deployment, making her work essential for students and engineers developing autonomous robot teams for search-and-rescue, exploration, and industrial automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3