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About

Byungchul An is a roboticist whose work spans motion planning, legged locomotion, and robotic manipulation for critical applications. His most influential contribution is an adaptive stepsize RRT planning algorithm for open-chain robots, which eliminates the tedious, problem-dependent trial-and-error of choosing a fixed stepsize in traditional RRT planners—a paper that has garnered 33 citations and become a reference point for adaptive sampling-based planning. In legged robotics, An proposed a simple, closed-form switching formula that determines optimal gait transition speeds for symmetrically arranged, even-legged robots, providing a principled method for when a robot should shift from walking to running. He has also advanced practical automation with an RFID-based localization algorithm enabling a plug-in electric vehicle recharging robot to autonomously dock, and tackled high-stakes environments by developing a humanoid robotic system for grasping and manipulation in nuclear decontamination tasks, reducing human exposure to radiation. Additionally, An contributed to medical robotics through the design optimization of AsclRod, a novel serial manipulator for microsurgery that offers improved stiffness over continuum alternatives. His work demonstrates a consistent drive to make robots more autonomous, efficient, and safe across diverse domains, from factory floors to operating rooms and hazardous waste sites.