Taehoon Kang
Papers
1
Total Citations
4
H-Index
1
About
Taehoon Kang is a robotics researcher whose work centers on autonomous navigation and obstacle avoidance, with a particular focus on dynamic environments like robot soccer. His 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 that adapts potential fields based on obstacle characteristics. This contribution addresses a critical challenge in robotics: enabling fast, safe movement in cluttered, unpredictable settings. While his citation count is modest, the work reflects a deep engagement with practical, high-stakes applications where computational efficiency and reliability are paramount. Kang’s research bridges theoretical control methods and applied robotics, offering insights valuable to students and engineers working on autonomous systems, from service robots to competitive platforms. His focus on obstacle-dependent strategies highlights a nuanced understanding of how robots can interpret and react to their surroundings, laying groundwork for more adaptive and intelligent navigation systems.
Research Focus
Key Achievements
Top Papers
- 1