Joohyun Park
Papers
1
Total Citations
12
H-Index
1
About
Joohyun Park is a robotics researcher whose work centers on improving the accuracy and reliability of autonomous mobile robot navigation, particularly in challenging, unstructured environments. His most-cited paper, "Correction Robot pose for SLAM based on Extended Kalman Filter in a Rough Surface Environment" (2009, 12 citations), addresses a critical problem in simultaneous localization and mapping (SLAM): the degradation of pose estimation when robots traverse rough or irregular surfaces. Park’s key contribution was the development of a dual extended Kalman filter (EKF) approach, which compensates for the uncertain kinematic model of tracked (caterpillar) robots. By adding a secondary correction filter, his method significantly enhances pose accuracy where standard EKF-SLAM fails. This work is particularly relevant for field robotics, such as search-and-rescue or planetary exploration, where terrain is unpredictable. While his citation count reflects a focused, specialized impact, Park’s research provides a practical solution to a persistent real-world challenge in mobile robotics, demonstrating a deep understanding of sensor fusion and state estimation under uncertainty.
Research Focus
Key Achievements
Top Papers
- 1