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...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| 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 |