Michelle Yi

Papers

Total Citations

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About

Michelle Yi is a leading researcher in robotic manipulation, with a focus on enabling robots to interact with articulated objects—such as cabinets, doors, and appliances—in unstructured environments. Her most notable contribution is the development of **AO-Grasp**, a novel grasp generation method that produces 6-DoF grasps specifically designed for articulated objects, allowing robots to perform actions like opening and closing drawers or doors. This work introduces both the **AO-Grasp Model**, which predicts functional grasps on movable parts, and the **AO-Grasp Dataset**, a large-scale collection of articulated object grasps that serves as a benchmark for the field. Though her paper is recent (2024), it has already garnered **5 citations**, signaling strong early impact. Yi’s research bridges the gap between perception and manipulation, offering practical solutions for household and industrial robots. Her work is particularly valuable for advancing autonomous systems that must handle dynamic, interactive environments. As a rising scholar, Yi’s contributions are poised to influence future research in dexterous manipulation, human-robot interaction, and embodied AI.