Papers
3
Total Citations
8
H-Index
2
About
Wan Xu is a rising researcher in the field of multi-robot systems, with a primary focus on cooperative simultaneous localization and mapping (SLAM) and intelligent path planning. His work addresses critical bottlenecks in multi-robot autonomy, particularly the excessive redundant computations and low processing efficiency in front-end loop detection, as well as the high computational complexity of global pose optimization. To solve these challenges, Xu introduced a novel sub-graph partitioning algorithm for multi-robot cooperative SLAM, which has already garnered 5 citations since its 2025 publication. In path planning, he developed the LAPGWO algorithm, an improved grey wolf optimizer that combines logistic mapping to overcome local optima and enhance convergence efficiency, earning his work 1 citation. Additionally, Xu has contributed to adaptive trajectory tracking control through path evaluation models. His research is particularly notable for its practical approach to real-world multi-robot coordination, offering scalable solutions that reduce computational overhead while maintaining accuracy. As an emerging voice in robotics, Xu’s work is paving the way for more efficient and robust multi-robot teams in applications ranging from search-and-rescue to industrial automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Adaptive trajectory tracking control based on path evaluation model2 citations · 2025
- 3