Look and Listen: A Multi-Sensory Pouring Network and Dataset for Granular Media from Human Demonstrations

Alexis Burns, Siyuan Xiang, Daewon Lee, Larry Jackel, Shuran Song, Volkan Isler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Humans have the ability to pour various media, both liquid and granular, to desired ends in various containers. We do this by using multiple senses simultaneously in a constant feedback loop to complete a pouring task. Combining multiple sensing modalities, similar to humans, could aid in robotic pouring control outside of a structured or industrial setting. We present a multi-sensory pouring dataset consisting of human pouring demonstrations of various granular media, coupled with two multi-sensory networks that estimate pouring rate and pouring average height. For both pouring metrics, a combined input of audio and visual data provides a lower median error than either the audio network or visual network. The multi-sensory network achieves a median error of 6.4 mm for average height estimation and 0.06 N/s for pouring rate estimation.

Original languageEnglish (US)
Title of host publication2022 IEEE International Conference on Robotics and Automation, ICRA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2519-2524
Number of pages6
ISBN (Electronic)9781728196817
DOIs
StatePublished - 2022
Externally publishedYes
Event39th IEEE International Conference on Robotics and Automation, ICRA 2022 - Philadelphia, United States
Duration: May 23 2022May 27 2022

Publication series

Name2022 International Conference on Robotics and Automation (ICRA)

Conference

Conference39th IEEE International Conference on Robotics and Automation, ICRA 2022
Country/TerritoryUnited States
CityPhiladelphia
Period5/23/225/27/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

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