Semantic world modeling using probabilistic multiple hypothesis anchoring

In order to successfully perform typical household tasks such as manipulation or navigation, domestic robots need an accurate description of the world they are operating in. Creating and maintaining such a description, in this work referred to as world model, is a non-trivial task in a domestic envi...

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Vydané v:	Robotics and autonomous systems Ročník 61; číslo 2; s. 95 - 105
Hlavní autori:	Elfring, J., van den Dries, S., van de Molengraft, M.J.G., Steinbuch, M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.02.2013
Predmet:	Anchoring Data association Domestic Mathematical models Multiple model tracking Probabilistic methods Probabilistic multiple hypothesis anchoring Probability theory Robots Tasks Tracking World modeling World modeling Probabilistic multiple hypothesis anchoring Anchoring Multiple model tracking Data association
ISSN:	0921-8890, 1872-793X
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Abstract	In order to successfully perform typical household tasks such as manipulation or navigation, domestic robots need an accurate description of the world they are operating in. Creating and maintaining such a description, in this work referred to as world model, is a non-trivial task in a domestic environment that typically has a high number of objects, and is unstructured and dynamically changing. This work introduces probabilistic multiple hypothesis anchoring to create and maintain a semantically rich world model using probabilistic anchoring. Multiple hypothesis tracking-based data association is included to be able to deal with ambiguous scenarios. Multiple model tracking is included to be able to easily incorporate different kinds of prior knowledge. ► We introduce probabilistic multiple hypothesis anchoring. ► Anchoring with multiple model tracking and multiple hypothesis based data association. ► Experimental validation of the approach in a series of challenging experiments. ► An analysis of the (im)possibilities of the method based on the assumptions made.
AbstractList	In order to successfully perform typical household tasks such as manipulation or navigation, domestic robots need an accurate description of the world they are operating in. Creating and maintaining such a description, in this work referred to as world model, is a non-trivial task in a domestic environment that typically has a high number of objects, and is unstructured and dynamically changing. This work introduces probabilistic multiple hypothesis anchoring to create and maintain a semantically rich world model using probabilistic anchoring. Multiple hypothesis tracking-based data association is included to be able to deal with ambiguous scenarios. Multiple model tracking is included to be able to easily incorporate different kinds of prior knowledge. ► We introduce probabilistic multiple hypothesis anchoring. ► Anchoring with multiple model tracking and multiple hypothesis based data association. ► Experimental validation of the approach in a series of challenging experiments. ► An analysis of the (im)possibilities of the method based on the assumptions made. In order to successfully perform typical household tasks such as manipulation or navigation, domestic robots need an accurate description of the world they are operating in. Creating and maintaining such a description, in this work referred to as world model, is a non-trivial task in a domestic environment that typically has a high number of objects, and is unstructured and dynamically changing. This work introduces probabilistic multiple hypothesis anchoring to create and maintain a semantically rich world model using probabilistic anchoring. Multiple hypothesis tracking-based data association is included to be able to deal with ambiguous scenarios. Multiple model tracking is included to be able to easily incorporate different kinds of prior knowledge.
Author	van de Molengraft, M.J.G. Elfring, J. Steinbuch, M. van den Dries, S.
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Cites_doi	10.1109/ICHR.2010.5686341 10.1609/aaai.v26i1.8212 10.1177/0278364911399340 10.1177/0278364903022002002 10.1109/MAES.2004.1263228 10.1142/S0218213012500121 10.1109/PerCom.2012.6199868 10.1109/7.532259 10.1016/j.robot.2008.10.024 10.1016/j.mechatronics.2010.05.011 10.1109/TAES.2003.1261119 10.1109/MFI.2010.5604454 10.1109/IROS.2010.5651280 10.1109/TAC.1979.1102177 10.1109/TPAMI.2006.247 10.1109/TAES.2005.1561886 10.1016/j.inffus.2003.03.003 10.1109/34.481539 10.1109/ICRA.2011.5980219 10.1016/S0921-8890(03)00021-6
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Snippet	In order to successfully perform typical household tasks such as manipulation or navigation, domestic robots need an accurate description of the world they are...
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SubjectTerms	Anchoring Data association Domestic Mathematical models Multiple model tracking Probabilistic methods Probabilistic multiple hypothesis anchoring Probability theory Robots Tasks Tracking World modeling
Title	Semantic world modeling using probabilistic multiple hypothesis anchoring
URI	https://dx.doi.org/10.1016/j.robot.2012.11.005 https://www.proquest.com/docview/1315697408
Volume	61
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