Papers

11

Total Citations

206

H-Index

6

About

Yeonsik Kang is a leading researcher in autonomous navigation, robotics, and intelligent vehicle control, with a focus on enabling safe and efficient operation in complex, real-world environments. His foundational work, "A Lidar-Based Decision-Making Method for Road Boundary Detection Using Multiple Kalman Filters" (108 citations), pioneered robust localization for mobile robots in GPS-denied urban areas. Dr. Kang has made significant contributions to model predictive control, as demonstrated in his highly cited paper on nonlinear MPC with obstacle avoidance (38 citations), and has advanced human-robot interaction through scalable, human-aware path planning for humanoid robots. His recent research integrates deep learning with sensor fusion, as seen in his 2024 work on dynamic occupancy grid maps using camera and LiDAR fusion (7 citations), pushing the boundaries of autonomous driving perception. Dr. Kang’s work also includes practical achievements, such as developing the autonomous vehicle VIROS for an international competition. With a career spanning over a decade, his research has garnered hundreds of citations, establishing him as a key figure in bridging theoretical control systems with real-world robotic and vehicular applications.

Research Focus

Key Achievements

6
H-Index
11
Papers
206
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
A Lidar-Based Decision-Making Method for Road Boundary Detection Using Multiple Kalman Filters
108 citations · 2012
📈 Most Prolific Year: 2012 (2 Papers)
🤝 Key Collaborators: 35
🏛 Institutions: Kookmin University, Korea Institute of Science and Technology, University of California, Berkeley

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago