Kwang-Ki Kim
Papers
2
Total Citations
5
H-Index
2
About
Kwang-Ki Kim is a rising researcher in robotics and optimal control, whose work bridges perception and decision-making for autonomous systems. His primary research areas include vision-based robot localization, optimal control theory, and constrained nonlinear dynamics. In a notable 2023 contribution, Kim developed a markerless method for robot-to-robot relative pose estimation using RGB-D data, enabling wheeled mobile robots to detect and localize each other without fiducial markers—a critical step toward scalable multi-robot coordination. This work, which has already garnered 3 citations, leverages machine vision for object detection and depth-based position estimation, offering a practical solution for dynamic environments. In 2022, Kim advanced control theory by extending interior point differential dynamic programming (IPDDP) to handle second-order conic constraints, a common structure in robotics and aerospace. His second-order conic IPDDP (SOC-IPDDP) provides a rigorous framework for solving nonlinear optimal control problems with safety-critical constraints, earning 2 citations. Together, these contributions demonstrate Kim’s ability to integrate perception and control, addressing real-world challenges in autonomous navigation. His work is particularly relevant for students and researchers interested in the intersection of computer vision and optimization-based control.
Research Focus
Key Achievements
Top Papers
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- 2