IROS 2020poster16 citations
Learning Motion Parameterizations of Mobile Pick and Place Actions from Observing Humans in Virtual Environments
Gayane Kazhoyan, Alina Hawkin, Sebastian Koralewski, Andrei Haidu, Michael Beetz
Abstract
In this paper, we present an approach and an implemented pipeline for transferring data acquired from observing humans in virtual environments onto robots acting in the real world, and adapting the data accordingly to achieve successful task execution. We demonstrate our pipeline by inferring seven different symbolic and subsymbolic motion parameters of mobile pick and place actions, which allows the robot to set a simple breakfast table. We propose an approach to learn general motion parameter models and discuss, which parameters can be learned at which abstraction level.
BibTeX
@inproceedings{iros2020_learningmotionpa,
title = {Learning Motion Parameterizations of Mobile Pick and Place Actions from Observing Humans in Virtual Environments},
author = {Gayane Kazhoyan and Alina Hawkin and Sebastian Koralewski and Andrei Haidu and Michael Beetz},
booktitle = {IROS 2020},
year = {2020}
}