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SLURP! Spectroscopy of Liquids Using Robot Pre-Touch Sensing

SLURP! Spectroscopy of Liquids Using Robot Pre-Touch Sensing

Nathaniel Hanson1* , Wesley Lewis2*, Kavya Puthuveetil2, Donelle Furline1, Akhil Padmanabha2, Taşkin Padir1 , Zackory Erickson2

Northeastern University1, Carnegie Mellon2


Liquids and granular media are pervasive throughout human environments. Their free-flowing nature causes people to constrain them into containers. We do so with thousands of different types of containers made out of different materials with varying sizes, shapes, and colors. In this work, we present a state-of-the-art sensing technique for robots to perceive what liquid is inside of an unknown container. We do so by integrating Visible to Near Infrared (VNIR) reflectance spectroscopy into a robot's end effector. We introduce a hierarchical model for inferring the material classes of both containers and internal contents given spectral measurements from two integrated spectrometers. To train these inference models, we capture and open source a dataset of spectral measurements from over 180 different combinations of containers and liquids. Our technique demonstrates over 85% accuracy in identifying 13 different liquids and granular media contained within 13 different containers. The sensitivity of our spectral readings allow our model to also identify the material composition of the containers themselves with 96% accuracy. Overall, VNIR spectroscopy presents a promising method to give household robots a general-purpose ability to infer the liquids inside of containers, without needing to open or manipulate the containers.

Slurp Gripper
(Left) Real-world assembly of the SLURP gripper. (Right) Exploded CAD rendering of SLURP gripper paddle showing inte- grated visible to near infrared spectrometers and active illumination associated physical gripper assembly.

Link to the Github

∗These authors contributed equally


  doi = {10.48550/ARXIV.2210.04941},
  url = {},
  author = {Hanson, Nathaniel and Lewis, Wesley and Puthuveetil, Kavya and Furline, Donelle and Padmanabha, Akhil and Padır, Taşkın and Erickson, Zackory},
  keywords = {Robotics (cs.RO), Signal Processing (eess.SP), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering},
  title = {SLURP! Spectroscopy of Liquids Using Robot Pre-Touch Sensing},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution 4.0 International}

Correspondence: hanson [.] n [@] northeastern [.] edu