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ESSMAC
2003
Springer

Simultaneous Localization and Surveying with Multiple Agents

14 years 17 days ago
Simultaneous Localization and Surveying with Multiple Agents
We apply a constrained Hidden Markov Model architecture to the problem of simultaneous localization and surveying from sensor logs of mobile agents navigating in unknown environments. We show the solution of this problem for the case of one robot and extend our model to the more interesting case of multiple agents, that interact with each other through proximity sensors. Since exact learning in this case becomes exponentially expensive, we develop an approximate method for inference using loopy belief propagation and apply it to the localization and surveying problem with multiple interacting robots. In support of our analysis, we report experimental results showing that with the same amount of data, approximate learning with the interaction signals outperforms exact learning ignoring interactions.
Sam T. Roweis, Ruslan Salakhutdinov
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where ESSMAC
Authors Sam T. Roweis, Ruslan Salakhutdinov
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