Younghwan Yoon
Papers
1
Total Citations
15
H-Index
1
About
Younghwan Yoon is a researcher whose work sits at the intersection of robotics, multi-agent systems, and intelligent motion planning. His most cited paper, "Analytic collision anticipation technology considering agents' future behavior" (2010, 15 citations), introduces a novel method for predicting when and where collisions will occur in configuration time space by explicitly modeling the future trajectories of agents. This approach moves beyond traditional reactive collision avoidance by enabling proactive, analytic anticipation—a significant conceptual leap for autonomous navigation in dynamic environments. Yoon’s contribution is particularly valuable for applications in swarm robotics, autonomous vehicles, and human-robot interaction, where anticipating the future behavior of multiple moving entities is critical for safe and efficient operation. Though his citation count reflects a focused, specialized impact, his work is recognized for addressing a fundamental gap in collision prediction: moving from immediate reaction to foresight. For students and researchers in robotics and AI, Yoon’s research offers a clear example of how integrating predictive modeling with geometric reasoning can transform motion planning from a reactive discipline into a forward-looking one.
Research Focus
Key Achievements
Top Papers
- 1