Ray W. Herrick Laboratories, Purdue University, IN • kim3686@purdue.edu
Hi! I am a Ph.D. candidate in Mechanical Engineering at Purdue University, specializing in robotics and automation in Multi-Scale Robotics and Automation Lab directed by Prof. David J. Cappelleri. My research is centered on advancing SLAM (Simultaneous Localization And Mapping) techniques and enhancing autonomous navigation in unstructured environments. Currently, my research focuses on the development of an innovative mobile robotic system designed for autonomous navigation and physical crop sampling in large-scale row-based cornfields. Starting in January 2025, I begin an internship at Nokia Bell Labs and contribute to design software and algorithms for computer vision-based drone localization in large-scale indoor environments.
During my internship, I will develop an optical flow-based multi-object tracking algorithm to identify and track landmarks in a large-scale indoor warehouse environment. Also, I will design and implement a factor graph-based SLAM algorithm. This SLAM solution integrates multi-object tracking outputs and visual-inertial odometry for robust drone navigation in the warehouse environment.
Kitae Kim, Aarya Deb, David J. Cappelleri, IEEE Robotics and Automation Letters (RA-L) (DOI: 10.1109/LRA.2025.3541335)
Kitae Kim, Aarya Deb, David J. Cappelleri, IEEE Robotics and Automation Letters (RA-L) (DOI: 10.1109/LRA.2024.3386466)
Aarya Deb, Kitae Kim, David J. Cappelleri, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (DOI: 10.1109/IROS55552.2023.10341516)
Minwoo Cho, Kitae Kim, Soohyun Cho, Seung-Mo Cho, Woojin Chung, Sensors (DOI: 10.3390/s23010438)
Kitae Kim, Aarya Deb, David J Cappelleri, IEEE Robotics and Automation Letters (RA-L) (DOI: 10.1109/LRA.2022.3187275)
Kitae Kim, Soohyun Cho, Woojin Chung, IEEE Robotics and Automation Letters (RA-L) (DOI: 10.1109/LRA.2021.3060406)
Kitae Kim, Soohyun Cho, Woojin Chung, the 15th Korea Robotics Society Annual Conference
Kitae Kim, Soohyun Cho, Woojin Chung, the 16th International Conference on Ubiquitous Robots (UR)
Our Mission is to create and translate to practice Internet of Thing (IoT) technologies for precision agriculture and to train and educate a diverse workforce that will address the societal grand challenge of food, energy, and water security for decades to come. In this research, I am focusing on developing autonomous ground-based robot which can navigate autonomously and do physical sampling for crop analysis in large-scale cornfields.
Our goal was to develop a technology that keeps high definition (HD) maps for autonomous vehicles up to date by using a large amount of low-cost low-quality crowdsourced data. I designed two main algorithms for various types of landmarks in the road environment by MATLAB and C++: Observation Learner module and Landmark Update module. My methods make it possible to determine which landmarks need to be registered in the updated maps. Throughout this project, I could realize the importance of accurate map management in the field of autonomous driving.