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, Rodriguez Garcia, Alberto
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article
Published: Institute of Electrical and Electronics Engineers (IEEE) 2019
Online Access:http://hdl.handle.net/1721.1/119860
https://orcid.org/0000-0002-1119-4512