RoboCAP: Robotic Classification and Precision Pouring of Diverse Liquids and Granular Media with Capacitive Sensing
Hu, Yexin, Gillespie, Alexandra, Padmanabha, Akhil, Puthuveetil, Kavya, Lewis, Wesley, Khokar, Karan, Erickson, Zackory
–arXiv.org Artificial Intelligence
Abstract--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 paralleljaw 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. Figure 1: Our capacitive sensing RoboCAP Gripper is mounted on an xArm 7; the highlighting shows two sensing arrays and I. Our sensing arrays and algorithms can classify the pictured containers and substances therein. We Identifying and manipulating liquid and granular media, can pour precise amounts of those substances using weight generally held in containers, are fundamental capabilities for changes over time during manipulation.
arXiv.org Artificial Intelligence
May-12-2024