Dong-Sig Han
Papers
2
Total Citations
10
H-Index
2
About
Dong-Sig Han is a robotics researcher whose work sits at the intersection of deep learning, multi-agent systems, and social robotics. His most influential contribution is the development of a **Perception-Action-Learning System for mobile social-service robots**, which integrates state-of-the-art deep learning into every module—from perception to action execution. This system demonstrated significant improvements in speed and robustness for real-world social service tasks, earning 8 citations and establishing a foundation for intelligent, human-interactive robots. More recently, Han has advanced the field of **multi-robot SLAM** with his work on robust map fusion using visual attention during multi-agent rendezvous. By addressing the challenge of independently built maps from different robots, his 2023 paper proposes a novel method for calculating accurate transformations between maps, a critical step for scalable cooperative robotics. Han’s research is notable for bridging theoretical deep learning with practical, deployable robotic systems, and his work continues to influence the development of autonomous agents that can perceive, learn, and collaborate in dynamic, human-centered environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robust Map Fusion with Visual Attention Utilizing Multi-agent Rendezvous2 citations · 2023