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About

Hyunwoo Nam is a robotics researcher whose work spans perception, locomotion, and manipulation, with a focus on making robots more capable, affordable, and safe. His most cited work, "Analysis and Noise Modeling of the Intel RealSense D435 for Mobile Robots" (61 citations), provides a critical evaluation of depth-sensing cameras as low-cost alternatives to LIDAR, offering essential noise models that have become a reference for mobile robotics researchers. Nam is perhaps best known for his pioneering contributions to buoyancy-assisted locomotion through the BALLU project. His paper "BALLU2: A Safe and Affordable Buoyancy Assisted Biped" introduces a novel robot that never falls, using helium-filled limbs to create a lightweight, inherently safe walking platform—a paradigm shift in bipedal design. He has also advanced task planning for dual-arm cooking robots using mixed-integer programming, demonstrating practical applications of optimization in robotics. More recently, Nam co-authored the guide for the RoboCup 2024 Adult-Sized Humanoid champions, showcasing his expertise in hardware, vision, and strategy. His work on the Surface Material Dataset for Robotics Applications further supports physically-aware robot perception. With a growing portfolio of impactful research, Nam is a rising figure in humanoid and assistive robotics.