Han-Soo Choi

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About

Han-Soo Choi is a robotics researcher whose work focuses on the foundational challenges of autonomous mobile robot (AMR) navigation, particularly under uncertain and unstructured environmental conditions. His key research areas include obstacle avoidance, path planning, and advanced control strategies for non-conventional robotic platforms. Choi’s most cited work, "Obstacle avoidance plan of autonomous mobile robot using fuzzy control" (2003), introduced a fuzzy logic-based approach to help robots navigate dynamic environments, a critical step toward safer and more adaptive automation. He further advanced the field with a neural network-based path planning design (2006), addressing the inherent difficulty of managing sensor fusion and skeletal control in AMRs when environmental conditions are unpredictable. In a notable later contribution (2015), Choi tackled the specific challenge of simultaneous path tracking and orientation control for three-wheeled omni-directional robots, demonstrating that conventional two-wheeled differential drive methods are inadequate for these platforms. By exploiting the omni-directional robot’s unconstrained movement capabilities, his controller achieved superior accuracy in both path following and orientation correction. Though his citation counts are modest, Choi’s work represents a dedicated, incremental effort to solve core problems in mobile robotics—from fuzzy and neural control to specialized kinematics—laying groundwork for more robust autonomous systems in real-world applications.