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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Bibliographic Details
Main Authors: Bauza Villalonga, Maria (Contributor), Rodriguez Garcia, Alberto (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2019-01-04T18:57:13Z.
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