The revisiting problem in mobile robot map building: A hierarchical Bayesian approach
Submitted by mkrainin on Tue, 2012-02-28 12:21
| Title | The revisiting problem in mobile robot map building: A hierarchical Bayesian approach |
| Publication Type | Conference Paper |
| Year of Publication | 2003 |
| Authors | Stewart B, Ko J, Fox D, Konolige K |
| Conference Name | UAI |
| Abstract | <p>We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-built portion of a map, or is exploring new territory. This is a difficult decision problem, requiring the probability of being outside of the current known map. To estimate this probability, we model the structure of a "typical" environment as a hidden Markov model that generates sequences of views observed by a robot navigating through the environment. A Dirichlet prior over structural models is learned from previously explored environments. Whenever a robot explores a new environment, the posterior over the model is estimated by Dirichlet hyperparameters. Our approach is implemented and tested in the context of multi-robot map merging, a particularly difficult instance of the revisiting problem. Experiments with robot data show that the technique yields strong improvements over alternative methods.</p> |
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| Citation Key | Ste03Rev |
Last changed Fri, 2012-03-16 18:03

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