Interactive Bayesian identification of kinematic mechanisms
This paper addresses the problem of identifying mechanisms based on data gathered while interacting with them. We present a decision-theoretic formulation of this problem, using Bayesian filtering techniques to maintain a distributional estimate of the mechanism type and parameters. In order to redu...
Main Authors: | Barragan, Patrick R., Lozano-Perez, Tomas, Kaelbling, Leslie P. |
---|---|
Other Authors: | Massachusetts Institute of Technology. Materials Processing Center |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2016
|
Online Access: | http://hdl.handle.net/1721.1/100723 https://orcid.org/0000-0003-4749-4979 https://orcid.org/0000-0002-8657-2450 https://orcid.org/0000-0001-6054-7145 |
Similar Items
-
Interactive Bayesian identification of kinematic mechanisms
by: Barragán, Patrick R
Published: (2015) -
Bayesian optimization with exponential convergence
by: Kawaguchi, Kenji, et al.
Published: (2018) -
A constraint-based method for solving sequential manipulation planning problems
by: Lozano-Perez, Tomas, et al.
Published: (2016) -
Unifying perception, estimation and action for mobile manipulation via belief space planning
by: Lozano-Perez, Tomas, et al.
Published: (2014) -
Integrated task and motion planning in belief space
by: Kaelbling, Leslie P., et al.
Published: (2014)