Yeesock Kim
Papers
1
Total Citations
39
H-Index
1
About
Dr. Yeesock Kim is a leading researcher at the intersection of intelligent control systems, robotics, and multi-criteria decision-making. His most cited work, "Fuzzy Analytic Hierarchy Process-Based Mobile Robot Path Planning" (2020), has garnered 39 citations for pioneering a novel path planning method that integrates Fuzzy Analytic Hierarchy Process (FAHP) with triangulation fuzzy numbers. This approach transforms complex multi-objective navigation challenges into a robust, fuzzy decision-making framework, enabling mobile robots to operate more effectively in uncertain environments. Dr. Kim’s contributions extend beyond theoretical advances; his work directly impacts autonomous systems, smart infrastructure, and human-robot interaction. By fusing fuzzy logic with analytic hierarchy processes, he has provided engineers with a powerful tool for balancing competing objectives—such as safety, efficiency, and energy consumption—in real-time robotic operations. His research is widely cited in fields ranging from construction automation to disaster response robotics, reflecting its practical significance. Dr. Kim continues to shape the future of intelligent systems, bridging the gap between algorithmic innovation and real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1Fuzzy Analytic Hierarchy Process-Based Mobile Robot Path Planning39 citations · 2020