Min Ho Choi

Papers

Total Citations

H-Index

About

Min Ho Choi is a robotics researcher focused on advancing localization techniques for outdoor mobile robots, with particular expertise in Kalman filtering methods for three-dimensional positioning. His work addresses the critical challenge of enabling robots to accurately determine their position in complex outdoor environments, moving beyond traditional 2D localization to incorporate altitude information. Choi's major contributions include developing both Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) based 3D localization methods that improve upon conventional approaches. His 2020 paper on UKF-based localization demonstrates how this method minimizes errors caused by linearization—a key limitation of standard EKF approaches—while his 2019 work on EKF-based localization pioneered the integration of encoder and inclination data for altitude estimation. Though his citation counts (3 and 2 respectively) reflect the emerging nature of his research, these foundational papers represent important steps toward practical outdoor robot navigation. Choi's work is particularly valuable for researchers developing autonomous systems that must operate reliably in real-world, three-dimensional environments where accurate positioning is essential for tasks ranging from agricultural robotics to autonomous delivery vehicles.