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About

Jong-Seob Won is a researcher whose work bridges the fields of robotics, autonomous systems, and human-machine interaction. His primary research areas include multi-robot navigation, robust control for autonomous underwater vehicles (AUVs), and bio-inspired robotic finger kinematics. Won’s most cited work, a 2020 study on multi-robot navigation, introduces a Fuzzy Analytic Hierarchy Process (FAHP) combined with cooperative game theory to optimize sub-goal selection for mobile robots, earning 17 citations and demonstrating a novel approach to multi-objective decision-making in dynamic environments. In 2021, he advanced robust control for AUVs by integrating sliding mode control with sliding perturbation observers (SMCSPO), achieving 10 citations for effectively mitigating nonlinearities and disturbances in underwater operations. Additionally, his 2019 geometry-based finger kinematic model, with 6 citations, offers a control-oriented framework for replicating natural human hand motion in robotic systems, contributing to the development of more dexterous artificial hands. Won’s work is notable for its practical applications in autonomous navigation and humanoid robotics, reflecting a commitment to solving real-world challenges in uncertain and complex environments.