Byoungsu Lee
Papers
1
Total Citations
2
H-Index
1
About
Byoungsu Lee is a researcher whose work centers on robotics, sensor fusion, and intelligent systems for home wellness applications. His most notable contribution is the development of a self-localization algorithm for indoor mobile robots, which integrates trilateration and triangulation through a fuzzy inference system. This collaborative approach, detailed in his 2014 study, enhances the accuracy of robot position estimation by combining the strengths of both methods—using RFID sensors and RSSI for trilateration, and angle-based data for triangulation. The algorithm is designed to improve trajectory control in home wellness robots, making them more reliable for tasks like navigation and assistance. Although his work has garnered 2 citations, it represents a foundational effort in applying fuzzy logic to sensor network collaboration, a technique that can be extended to other autonomous systems. Lee’s research addresses a critical challenge in indoor robotics: achieving precise self-localization without expensive hardware. His work is particularly relevant for students and researchers interested in practical sensor fusion, human-robot interaction, and the integration of soft computing methods in real-world robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1