Multi-robot Markov random fields

8 years 4 months ago
Multi-robot Markov random fields
We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selection. The MRF model is well-suited to domains in which the joint probability over latent (action) and observed (perceived) variables can be factored into pairwise interactions between these variables. Specifically, these interactions occur through functions that evaluate "local evidence" between an observed and latent variable and"compatibility" between a pair of latent variables. For multi-robot coordination, we cast local evidence functions as the computation for an individual robot's action selection from its local observations and compatibility as the dependence in action selection between a pair of robots. We describe how existing methods for multi-robot coordination (or at least a non-exhaustive subset) fit within an MRF-based model and how they conceptually unify. Further, we offe...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where ATAL
Authors Jesse Butterfield, Odest Chadwicke Jenkins, Brian P. Gerkey
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