Young-Hak Mo
Papers
1
Total Citations
3
H-Index
1
About
Young-Hak Mo’s research centers on multi-agent robotics, sensor fusion, and autonomous navigation in unknown environments. His most cited work, “Obstacle Avoidance Method for Multi-Agent Robots Using IR Sensor and Image Information” (2012, 3 citations), introduces a pioneering approach that integrates infrared sensors with vision systems for real-time obstacle detection and path planning. By enabling robots to share spatial information collaboratively, Mo’s method allows multi-agent systems to select optimal trajectories, significantly improving efficiency and safety in industrial and scout robot applications. This contribution addresses critical challenges in decentralized robotics, where coordination and environmental awareness are paramount. While his citation count remains modest, Mo’s work lays foundational groundwork for advancing autonomous multi-robot coordination. His research continues to influence developments in sensor fusion and cooperative navigation, offering practical solutions for dynamic, obstacle-rich settings. For students and researchers exploring multi-agent systems, Mo’s integration of low-cost IR sensors with image processing provides a scalable, accessible framework for real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1