Factor Graphs for Robot Perception
Factor Graphs for Robot Perception reviews the use of factor graphs for the modeling and solving of large-scale inference problems in robotics. Factor graphs are a family of probabilistic graphical models, other examples of which are Bayesian networks and Markov random fields, well known from the statistical modeling and machine learning literature. They provide a powerful abstraction that gives insight into particular inference problems, making it easier to think about and design solutions, and write modular software to perform the actual inference. This book illustrates their use in the simultaneous localization and mapping problem and othe…
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Produktdetails
Weitere Autoren: Kaess, Michael
- ISBN: 978-1-68083-326-3
- EAN: 9781680833263
- Produktnummer: 24002968
- Verlag: Now Publishers Inc
- Sprache: Englisch
- Erscheinungsjahr: 2017
- Seitenangabe: 162 S.
- Masse: H23.4 cm x B15.6 cm x D0.9 cm 257 g
- Abbildungen: Paperback
- Gewicht: 257
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