Liquids and granular media are pervasive throughout human environments, yet remain particularly challenging for robots to sense and manipulate precisely. In this work, we present a systematic approach at integrating capacitive sensing within robotic end effectors to enable robust sensing and precise manipulation of liquids and granular media. We introduce the parallel-jaw RoboCAP Gripper with embedded capacitive sensing arrays that enable a robot to directly sense the materials and dynamics of liquids inside of diverse containers, including some visually opaque. When coupled with model-based control, we demonstrate that the proposed system enables a robotic manipulator to achieve state-of-the-art precision pouring accuracy for a range of substances with varying dynamics properties. Code, designs, and build details are available on the project website.
View on arXiv@article{hu2025_2405.07423,
title={ RoboCAP: Robotic Classification and Precision Pouring of Diverse Liquids and Granular Media with Capacitive Sensing },
author={ Yexin Hu and Alexandra Gillespie and Akhil Padmanabha and Kavya Puthuveetil and Wesley Lewis and Karan Khokar and Zackory Erickson },
journal={arXiv preprint arXiv:2405.07423},
year={ 2025 }
}