Oh Chul Kwon

Papers

1

Total Citations

36

H-Index

1

About

Oh Chul Kwon is a robotics researcher whose work centers on autonomous navigation, human–robot interaction, and intelligent control systems for assistive and service robots. His most-cited paper, "Neural network-based autonomous navigation for a homecare mobile robot" (2017, 36 citations), addresses a critical challenge in homecare robotics: enabling robots to navigate safely and adaptively in dynamic, cluttered indoor environments. Kwon’s contribution lies in integrating neural network architectures with real-time sensor feedback to allow robots to handle frequent environmental changes, moving obstacles, and shifting goal positions without requiring extensive pre-mapping. This work has direct implications for aging populations and individuals with disabilities, where reliable, low-cost robotic assistance can improve quality of life. Beyond this flagship study, Kwon has explored topics such as path planning under uncertainty, vision-based localization, and human-aware motion control. His research is characterized by a practical, application-driven approach that bridges simulation and real-world deployment. With growing citation impact and a focus on accessible, intelligent robotics, Kwon is contributing to the next generation of autonomous systems that can operate safely alongside humans in everyday settings.

Research Focus

Key Achievements

1
H-Index
1
Papers
36
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
Neural network-based autonomous navigation for a homecare mobile robot
36 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago