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 language | English (US) |
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Title of host publication | 2022 IEEE International Conference on Robotics and Automation, ICRA 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2519-2524 |
Number of pages | 6 |
ISBN (Electronic) | 9781728196817 |
DOIs | |
State | Published - 2022 |
Externally published | Yes |
Event | 39th IEEE International Conference on Robotics and Automation, ICRA 2022 - Philadelphia, United States Duration: May 23 2022 → May 27 2022 |
Publication series
Name | 2022 International Conference on Robotics and Automation (ICRA) |
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Conference
Conference | 39th IEEE International Conference on Robotics and Automation, ICRA 2022 |
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Country/Territory | United States |
City | Philadelphia |
Period | 5/23/22 → 5/27/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.