Papers
16
Total Citations
236
H-Index
8
About
Changwon Kim is a robotics researcher whose work spans mobile robot navigation, motion control, and the integration of artificial intelligence into autonomous systems. Over more than a decade of contributions, Kim has established a distinctive research identity centered on intelligent decision-making frameworks for mobile robots, most notably developing and refining Fuzzy Analytic Hierarchy Process (FAHP)-based path planning methods that enable robots to navigate complex, dynamic environments through multi-objective optimization. His bio-inspired control strategies for omni-wheel and mecanum-wheeled robots have demonstrated robust real-world performance in logistics and industrial settings, earning significant scholarly attention with individual papers accumulating up to 44 citations. Kim's research has increasingly expanded into applied domains, including patient transfer robots, autonomous forklifts in smart warehouses, and worker-following systems for smart factories, bridging theoretical innovation with practical deployment. Most recently, his survey on robot intelligence with large language models (47 citations) reflects a timely pivot toward exploring how LLMs like ChatGPT can enhance robotic planning and natural language understanding. Collectively, Kim's body of work represents a coherent and evolving research program that positions autonomous robotics at the intersection of classical control theory, fuzzy logic, and cutting-edge AI.
Research Focus
Key Achievements
Top Papers
- 1A Survey of Robot Intelligence with Large Language Models47 citations · 2024
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- 3Fuzzy Analytic Hierarchy Process-Based Mobile Robot Path Planning39 citations · 2020
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- 8A Bio Inspired Control Strategy for a Mecanum-Wheeled Robot Position Control10 citations · 2017
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