Carolyn Matl

Papers

Total Citations

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About

Carolyn Matl is a roboticist whose research focuses on enabling robots to perceive and manipulate complex, non-rigid materials—liquids, granular media, and deformable solids—that are essential for real-world applications in industries like agriculture, manufacturing, and pharmaceuticals. Her most-cited work, “Haptic Perception of Liquids Enclosed in Containers” (2019, 22 citations), tackles a critical gap in robotic pouring: when visual sensing fails due to opaque containers, Matl’s haptic approach allows robots to infer liquid properties through touch, advancing service robot autonomy. In “Deformable Elasto-Plastic Object Shaping using an Elastic Hand and Model-Based Reinforcement Learning” (2021, 18 citations), she pioneers the manipulation of clay-like materials, a notoriously challenging domain, by combining an elastic gripper with reinforcement learning to shape objects—a breakthrough for industrial and home tasks. Her work “Inferring the Material Properties of Granular Media for Robotic Tasks” (2020, 3 citations) further extends this expertise, developing simulation tools for materials like cereal grains and pills. Matl’s contributions are notable for bridging perception and manipulation in under-explored areas, with her research directly impacting the design of robots that can handle everyday and industrial materials with human-like dexterity.