Dayeon Lee
Papers
1
Total Citations
4
H-Index
1
About
Dayeon Lee is a robotics researcher whose work focuses on intelligent navigation and obstacle avoidance, particularly in dynamic, multi-agent environments like robot soccer. Her most-cited paper, "Local Obstacle Avoidance Using Obstacle-Dependent Gaussian Potential Field for Robot Soccer" (2016), introduces a novel approach to real-time path planning by adapting the traditional potential field method to account for the shape and motion of obstacles. This contribution is critical for enabling autonomous robots to maneuver safely and efficiently in crowded, unpredictable settings—a key challenge in competitive robotics and autonomous systems. With 4 citations, this work has laid groundwork for further studies in adaptive potential fields and has been referenced in subsequent research on mobile robot control and swarm robotics. Lee’s research bridges theoretical control algorithms with practical applications, offering insights that are valuable for students and engineers developing autonomous vehicles, service robots, and robotic sports platforms. Her work exemplifies how targeted, scenario-specific solutions can advance broader fields in robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1