Daehyun Kyoung
Papers
1
Total Citations
3
H-Index
1
About
Daehyun Kyoung is a robotics researcher whose work focuses on advancing multi-robot coordination and autonomous navigation in complex, human-shared environments. His most cited paper, "Learning to Improve Multi-Robot Hallway Navigation" (2020), introduces a novel learning-based approach to enable multiple robots to efficiently and safely navigate narrow, dynamic spaces like hallways. This work addresses a critical challenge in real-world robotics—how to avoid deadlocks and collisions while maintaining smooth traffic flow—by combining reinforcement learning with decentralized control policies. Though early in his career, Kyoung's contributions are already influencing the design of more intelligent, cooperative robotic systems for logistics, service, and industrial applications. His research bridges the gap between theoretical multi-agent planning and practical deployment, demonstrating how robots can learn to negotiate shared spaces without centralized coordination. With 3 citations to date, this foundational paper marks a promising start for a researcher poised to make significant strides in autonomous navigation and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1Learning to Improve Multi-Robot Hallway Navigation.3 citations · 2020