Hyun-Chang Yang
Papers
1
Total Citations
11
H-Index
1
About
Hyun-Chang Yang is a pioneering researcher in swarm robotics and intelligent multi-agent systems, with a focus on integrating machine learning with distributed robotic control. 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 algorithm that combines polygon-based Q-learning with parallel support vector machines for efficient object search and tracking in large-scale robot swarms. In this landmark study, Yang demonstrated the algorithm's scalability by deploying 100 mobile robots in a complex environment with 200 obstacles and 10 target objects, showcasing robust performance in real-world hallway navigation scenarios. This work has been foundational for researchers exploring reinforcement learning in multi-robot systems, particularly for applications in search-and-rescue, warehouse automation, and environmental monitoring. Yang's contributions lie at the intersection of reinforcement learning, swarm intelligence, and parallel computing, offering practical solutions for coordinating large robot teams under constrained conditions. His research continues to influence the development of adaptive, decentralized control strategies for autonomous systems operating in dynamic, obstacle-rich environments.
Research Focus
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Top Papers
- 1