Semantic world modeling using probabilistic multiple hypothesis anchoring

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25 Citaties (Scopus)

Uittreksel

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 diferent kinds of prior knowledge.
TaalEngels
Pagina's95-105
TijdschriftRobotics and Autonomous Systems
Volume61
Nummer van het tijdschrift2
DOI's
StatusGepubliceerd - 2013

Vingerafdruk

Probabilistic Modeling
Semantics
Data Association
Robot Navigation
Multiple Models
Ambiguous
Prior Knowledge
Probabilistic Model
Manipulation
Navigation
Robots
Scenarios
Model
Object
Statistical Models

Citeer dit

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Semantic world modeling using probabilistic multiple hypothesis anchoring. / Elfring, J.; Dries, van den, S.; Molengraft, van de, M.J.G.; Steinbuch, M.

In: Robotics and Autonomous Systems, Vol. 61, Nr. 2, 2013, blz. 95-105.

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

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