Donelle Furline

Papers

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About

Donelle Furline is a roboticist whose work bridges the gap between tactile sensing and autonomous manipulation of everyday materials. Her primary research focuses on enabling robots to perceive and interact with liquids, granular media, and deformable objects—substances that have historically challenged robotic systems due to their unpredictable physical properties. In her landmark paper "SLURP! Spectroscopy of Liquids Using Robot Pre-Touch Sensing" (2023, 9 citations), Furline introduced a novel pre-touch sensing technique that allows robots to identify liquid contents and container materials before physical contact, using spectroscopy to analyze optical signatures. This work represents a significant leap in pre-grasp perception, enabling robots to make informed decisions about how to handle filled containers. Furline’s contributions have direct implications for domestic robotics, laboratory automation, and food service applications. Her approach to combining near-range sensing with material classification has been recognized as a foundational step toward robots that can safely and efficiently manage the diverse, fluid-filled objects that populate human environments.