Ho Sang Kwon
Papers
1
Total Citations
2
H-Index
1
About
Ho Sang Kwon is a robotics researcher whose work focuses on autonomous navigation and human-robot interaction, particularly in dynamic and complex environments. His most-cited paper, "Person tracking with a mobile robot using particle filters in complex environment" (2005), addresses the critical challenge of enabling mobile robots to reliably follow a person in real time, despite unpredictable human motion and environmental clutter. By applying particle filters—a probabilistic approach to state estimation—Kwon’s work provides a robust solution for person-following, balancing real-time performance with adaptability to sudden movement changes. This contribution is foundational for service robots, assistive technologies, and autonomous systems that require close human collaboration. While his citation count is modest, the research addresses a core problem in mobile robotics: achieving stable, responsive tracking without sacrificing computational efficiency. Kwon’s work underscores the importance of probabilistic methods in bridging the gap between theoretical robotics and practical deployment, offering a stepping stone for subsequent advances in human-aware navigation and multi-sensor fusion. His contributions remain relevant for researchers developing robots that operate safely alongside people in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1