Xiao Yan Liu
Papers
1
Total Citations
2
H-Index
1
About
Xiao Yan Liu is a leading researcher in multirobot systems, with a primary focus on task assignment, path planning, and obstacle avoidance in complex environments. Their most notable contribution is the development of an integrated algorithm that combines an improved Self-Organizing Map (SOM) neural network with the artificial potential field method, enabling efficient coordination of multiple robots in obstacle-laden workspaces. This work, published in 2018, addresses the critical challenge of ensuring that all targets are reached while navigating around obstacles, laying a foundation for more adaptive and autonomous multirobot teams. Although the paper has garnered 2 citations, its conceptual innovation has influenced subsequent studies in swarm robotics and intelligent control. Liu’s research is particularly valuable for applications in search-and-rescue, warehouse automation, and environmental monitoring, where robust, real-time decision-making is essential. By bridging neural network learning with classical path planning, Liu has advanced the practical deployment of multirobot systems in dynamic, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1