A probabilistic data-driven model for planar pushing
This paper presents a data-driven approach to model planar pushing interaction to predict both the most likely outcome of a push and its expected variability. The learned models rely on a variation of Gaussian processes with input-dependent noise called Variational Heteroscedastic Gaussian processes...
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Format: | Article |
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Institute of Electrical and Electronics Engineers (IEEE)
2019
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Online Access: | http://hdl.handle.net/1721.1/119860 https://orcid.org/0000-0002-1119-4512 |