Beobkyoon Kim
Papers
6
Total Citations
266
H-Index
5
About
Beobkyoon Kim is a leading researcher in robot motion planning and dynamics, whose work bridges the gap between differential geometry and practical robotics. His primary research areas include constrained motion planning, continuum robot shape sensing, and geometric algorithms for robot dynamics. Kim’s most influential contribution is the Tangent Bundle RRT (TB-RRT) algorithm, which enables efficient motion planning on curved configuration space manifolds—a fundamental challenge for robots with complex kinematics. This work, published in 2014, has garnered 95 citations and remains a cornerstone in constrained motion planning. He also pioneered methods for optimizing curvature sensor placement in continuum robots, achieving 76 citations by enabling fast, accurate shape sensing without relying on error-prone kinematic models. His tutorial review on geometric algorithms for robot dynamics, which systematically applies Lie group theory to rigid-body motion, has been cited 55 times and is widely used as a reference by researchers and students alike. Kim’s work is notable for its mathematical rigor and practical impact, offering elegant solutions to real-world robotics problems. His research continues to shape how robots navigate and interact with complex environments.
Research Focus
Key Achievements
Top Papers
- 1Tangent bundle RRT: A randomized algorithm for constrained motion planning95 citations · 2014
- 2
- 3Geometric Algorithms for Robot Dynamics: A Tutorial Review55 citations · 2018
- 4Tangent space RRT: A randomized planning algorithm on constraint manifolds32 citations · 2011
- 5Movement primitives for three-legged locomotion over uneven terrain5 citations · 2009
- 6