Snag-Wook Seo
Papers
1
Total Citations
11
H-Index
1
About
Snag-Wook Seo is a pioneering researcher in swarm robotics and intelligent multi-agent systems, with a focus on developing scalable, real-time coordination algorithms. His most cited work, "Object tracking algorithm of Swarm Robot System for using Polygon based Q-learning and parallel SVM" (2008, 11 citations), introduces a novel hybrid approach that combines polygon-based Q-learning with parallel support vector machines for efficient object search and tracking in large-scale robotic swarms. Seo’s major contribution lies in demonstrating how reinforcement learning and machine learning can be integrated to enable decentralized decision-making among hundreds of robots. In this landmark study, he organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects, showcasing the algorithm’s robustness in cluttered, dynamic hallways. This work has influenced subsequent research in multi-robot coordination, particularly in applications like search-and-rescue and automated logistics. Seo’s achievements highlight his ability to bridge theoretical machine learning with practical swarm robotics, offering a scalable framework for autonomous systems operating in complex, obstacle-rich environments.
Research Focus
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Top Papers
- 1