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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

Year
2022
Citations
4

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.

Keywords

Sensory systemComputer scienceTask (project management)ModalitiesStimulus modalityWord error rateArtificial intelligenceComputer visionEngineering

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