Minsoo Kim
Papers
1
Total Citations
54
H-Index
1
About
Minsoo Kim is a researcher specializing in autonomous systems, motion planning, and robotics, with a particular focus on path planning algorithms for autonomous vehicles. His most notable contribution is the development of TargetTree-RRT*, a continuous-curvature path planning algorithm designed to address the computational challenges of autonomous parking in complex, constrained environments. By innovating upon the foundational Rapidly-exploring Random Tree (RRT) framework, Kim's work significantly reduces planning time in narrow parking scenarios — a persistent bottleneck in real-world autonomous vehicle deployment. This research has garnered 54 citations since its 2022 publication, reflecting strong recognition within the robotics and intelligent transportation communities. Kim's work sits at the intersection of computational efficiency and practical applicability, bridging theoretical algorithmic advancements with the demanding requirements of real-world autonomous driving systems. His contributions are particularly valuable for researchers and engineers working on last-mile autonomy challenges, where precise maneuvering in tight spaces remains technically demanding. As autonomous vehicle technology continues to mature, Kim's algorithmic innovations represent a meaningful step toward safer and more efficient self-parking systems.
Research Focus
Key Achievements
Top Papers
- 1