Kyu Ree Kim
Papers
1
Total Citations
2
H-Index
1
About
Kyu Ree Kim is a robotics researcher whose work centers on autonomous navigation, sensor fusion, and intelligent control systems for mobile robots. Her most cited paper, "ROS-based Control System for Localization and Object Identification of Indoor Self-driving Mobile Robot" (2021, 2 citations), presents a complete robotic system designed for automated logistics—specifically, a robot that can classify boxes by region and company, avoid obstacles in real time, and transport goods to target locations. Kim’s key contribution lies in integrating the Robot Operating System (ROS) with an OpenCR low-level controller for motor and sensor management, while employing an Adaptive Monte Carlo Localization (AMCL) algorithm that fuses IMU and encoder odometry data for precise indoor positioning. This work demonstrates her ability to combine hardware control with sophisticated probabilistic localization, a critical challenge in autonomous warehouse robotics. Although early in her citation impact, Kim’s research addresses practical, industry-relevant problems in logistics automation, positioning her as an emerging contributor to the field of intelligent, self-driving mobile systems.
Research Focus
Key Achievements
Top Papers
- 1