Ling Wen
Papers
1
Total Citations
2
H-Index
1
About
Ling Wen is a rising researcher in multi-robot systems and artificial intelligence, with a focus on developing intelligent navigation and coordination strategies. Their most notable contribution is the paper "Queue Formation and Obstacle Avoidance Navigation Strategy for Multi-Robot Systems Based on Deep Reinforcement Learning" (2025), which addresses a critical challenge in robotics: enabling multiple robots to work together safely and efficiently in complex environments. By integrating deep reinforcement learning with queue formation protocols, Wen’s work provides a novel framework for robots to avoid collisions while maintaining coordinated movement—an essential capability for applications in warehouse automation, search-and-rescue missions, and autonomous exploration. Although this paper has garnered 2 citations to date, its forward-looking approach signals significant potential for impact in the field. Wen’s research bridges the gap between theoretical reinforcement learning and practical multi-agent systems, offering scalable solutions that could transform how robots collaborate in dynamic, obstacle-rich settings. As robotics continues to evolve, Ling Wen’s contributions are poised to influence future developments in autonomous navigation and swarm intelligence.
Research Focus
Key Achievements
Top Papers
- 1