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About

Woong-Gie Han is a robotics and intelligent systems researcher whose work spans autonomous robot control, adaptive learning algorithms, and mobile robot navigation. His most recognized contribution, "An Adaptive PID Learning Control of Robot Manipulators" (2000), has garnered over 100 citations, establishing him as a notable voice in the development of intelligent control strategies that combine adaptive PID feedback with feedforward learning schemes to improve the precision and stability of robotic motion. Building on this foundation, Han extended his adaptive PID framework to periodic robot motion tasks, demonstrating its versatility across dynamic operational contexts. A significant thread throughout Han's research is the application of genetic algorithms to mobile robot navigation. His 2002 work on genetic algorithm-based path planning and dynamic obstacle avoidance — cited 55 times — introduced an efficient coding technique that accelerates genetic search for real-time path generation, a meaningful advance for practical robotics deployment. He further applied this approach to the challenging domain of robot soccer, developing intelligent navigation architectures capable of coordinating micro-robots in dynamic, multi-agent environments. Together, Han's contributions reflect a coherent research vision: making robots smarter, faster, and more adaptable through the integration of evolutionary computation and learning-based control.