Yo-Seop Hwang
Papers
12
Total Citations
58
H-Index
5
About
Yo-Seop Hwang is a robotics and autonomous systems researcher whose work centers on mobile robot navigation, 3D map building, and sensor-based localization. Over the course of his career, Hwang has made significant contributions to solving practical challenges in robot perception, particularly through the development of cost-effective alternatives to expensive sensing hardware. His most-cited work (2013, 11 citations) introduced an Extended Kalman Filter-based outdoor positioning system leveraging multiple GPS receivers to overcome the instantaneous signal errors that typically degrade positioning accuracy. A recurring theme across his research is the creative use of Laser Range Finders (LRF) to construct reliable 2D and 3D environmental maps, including scenarios involving slanted and uneven surfaces — a limitation many prior approaches failed to address. His noise-filtering contributions, including hybrid median and superposition median filter techniques, improved the quality of LRF data for map building. Hwang also explored iterative closest point (ICP) algorithms for motion-robust 2D mapping and applied SURF-based algorithms for indoor localization. Notably, he extended his sensor expertise into agricultural robotics, contributing to 3D plant leaf segmentation using Kinect cameras. With cumulative citations across ten publications, Hwang's body of work reflects a consistent focus on making autonomous robot navigation more robust, accessible, and practically deployable.
Research Focus
Key Achievements
Top Papers
- 1EKF Based Outdoor Positioning System using Multiple GPS Receivers11 citations · 2013
- 2
- 33D map building for a moving based on mobile robot6 citations · 2014
- 4
- 5Robust 3D map building for a mobile robot moving on the floor5 citations · 2015
- 6
- 7
- 82D grid map building using ICP algorithm and line extraction3 citations · 2014
- 9
- 10