Dynamic Bayesian network for semantic place classification in mobile robotics

@article{Premebida2017DynamicBN,
  title={Dynamic Bayesian network for semantic place classification in mobile robotics},
  author={Cristiano Premebida and Diego R. Faria and Urbano Nunes},
  journal={Auton. Robots},
  year={2017},
  volume={41},
  pages={1161-1172}
}
In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called Dynamic Bayesian Mixture Model (DBMM), which is an improved variation of the Dynamic Bayesian Network (DBN). More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a… CONTINUE READING
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