Seongwoo Jang
Papers
1
Total Citations
8
H-Index
1
About
Seongwoo Jang is a researcher whose work centers on mobile robotics, with a particular focus on the localization and navigation of automated guided vehicles (AGVs) in industrial environments. His key contributions lie in sensor fusion and probabilistic filtering, where he has developed methods to enhance the accuracy and reliability of robot positioning. His most cited work, "A study on integration of particle filter and dead reckoning for efficient localization of automated guided vehicles" (2015), proposes a novel approach that combines particle filtering with dead-reckoning techniques to overcome the limitations of individual localization methods. This integration allows AGVs to maintain precise position estimates even in dynamic factory settings, directly addressing the challenge of human-robot collaboration in shared workspaces. With 8 citations, this paper has served as a foundational reference for researchers working on robust indoor localization for industrial robotics. Jang’s work is particularly notable for its practical orientation, bridging theoretical advances in probabilistic robotics with real-world deployment needs in factory automation.
Research Focus
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Top Papers
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