Yi‐Shiang Huang

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About

Yi-Shiang Huang is a rising researcher in embodied AI and human-robot interaction, with a focus on enabling robots to navigate and assist in complex, human-centric environments. Their work centers on two key areas: spatial intelligence for autonomous navigation and cognitive robotics for home care. Huang’s major contribution lies in developing systems that allow robots to operate effectively without requiring extensive pre-mapping or technical expertise from users. Their 2024 paper on “Spatial Graph-Based Localization and Navigation on Scaleless Floorplan” (4 citations) introduces a novel method that mimics human-like navigation using only a simple floorplan, bypassing the need for traditional SLAM or teleoperation—a significant step toward making robots accessible for everyday use. In parallel, their work on “Object-Goal Navigation of Home Care Robot Based on Human Activity Inference and Cognitive Memory” (2 citations) tackles the pressing challenge of supporting older adults with cognitive decline. By integrating human activity inference with cognitive memory, Huang’s system enables robots to proactively locate desired objects, blending perception, reasoning, and memory. Though early in their career, Huang’s research directly addresses real-world deployment hurdles, promising more intuitive, helpful robots for aging populations and non-expert users alike.