Dongkyoung Chwa

Ajou University, Seoul National University

Papers

24

Total Citations

1,060

H-Index

11

About

Dongkyoung Chwa is a prominent robotics and control systems researcher whose work has profoundly shaped the fields of mobile robot control, multi-robot coordination, and intelligent control systems. His research focuses on wheeled mobile robots, formation control, obstacle avoidance, and advanced nonlinear control methodologies, with a particular emphasis on addressing real-world uncertainties and constraints. Chwa's most celebrated contribution, a decentralized behavior-based formation control framework for multi-robot systems incorporating obstacle avoidance (2017, 236 citations), established a foundational approach to coordinated autonomous navigation. His 2010 backstepping-like feedback linearization method for differential-drive robots (171 citations) introduced an elegant solution to the long-standing challenge of nonholonomic motion control, while his fuzzy adaptive tracking control framework (2011, 128 citations) extended this work to robots subject to slippage and kinematic disturbances — conditions frequently encountered in practical deployments. His innovative application of interval type-2 fuzzy neural networks for obstacle avoidance (2014, 138 citations) demonstrated a sophisticated fusion of intelligent computing with classical control theory. More recently, Chwa has advanced sliding-mode disturbance observer techniques and visual servoing methods for omnidirectional robots. With hundreds of citations across a decade of sustained contributions, his research continues to significantly influence autonomous robotics and robust control design worldwide.

Research Focus

Key Achievements

11
H-Index
24
Papers
1,060
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
Decentralized behavior-based formation control of multiple robots considering obstacle avoidance
236 citations · 2017
📈 Most Prolific Year: 2009 (4 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: Ajou University, Seoul National University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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