Semantic Localization through Propagation of Scene Information in a Hierarchical Model
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00334776" target="_blank" >RIV/68407700:21230/19:00334776 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/68407700:21730/19:00334776
Výsledek na webu
<a href="https://doi.org/10.1109/ECMR.2019.8870972" target="_blank" >https://doi.org/10.1109/ECMR.2019.8870972</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ECMR.2019.8870972" target="_blank" >10.1109/ECMR.2019.8870972</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Semantic Localization through Propagation of Scene Information in a Hierarchical Model
Popis výsledku v původním jazyce
The success of mobile robots, and particularly these coexisting with humans, relies on the ability to understand human environments. Representing the world and analysing spaces in a similar way to humans will enhance their comprehension and enable higher abstraction capabilities and interactions. The purpose of this work is to develop a localization framework that takes into account the different scenes common in a human environment and a hierarchical model of the environment. A probabilistic model for recognizing scenes is employed to determine the scene in which the robot is located. To allow that, the information about the objects and the relationships between them are considered. Besides that, a hierarchical model formed by different topological representations according to different levels of abstraction is proposed. Localization is performed at different levels to improve the localization accuracy. In this work, scene information is used to improve the localization of a mobile robot in a hierarchical model using hidden Markov models. The experiments of our framework working in real environments uphold the usefulness of the inclusion of the understanding and abstraction of the environment in localization.
Název v anglickém jazyce
Semantic Localization through Propagation of Scene Information in a Hierarchical Model
Popis výsledku anglicky
The success of mobile robots, and particularly these coexisting with humans, relies on the ability to understand human environments. Representing the world and analysing spaces in a similar way to humans will enhance their comprehension and enable higher abstraction capabilities and interactions. The purpose of this work is to develop a localization framework that takes into account the different scenes common in a human environment and a hierarchical model of the environment. A probabilistic model for recognizing scenes is employed to determine the scene in which the robot is located. To allow that, the information about the objects and the relationships between them are considered. Besides that, a hierarchical model formed by different topological representations according to different levels of abstraction is proposed. Localization is performed at different levels to improve the localization accuracy. In this work, scene information is used to improve the localization of a mobile robot in a hierarchical model using hidden Markov models. The experiments of our framework working in real environments uphold the usefulness of the inclusion of the understanding and abstraction of the environment in localization.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
20204 - Robotics and automatic control
Návaznosti výsledku
Projekt
<a href="/cs/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotika pro Průmysl 4.0</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of European Conference on Mobile Robots
ISBN
978-1-7281-3605-9
ISSN
—
e-ISSN
—
Počet stran výsledku
6
Strana od-do
—
Název nakladatele
Czech Technical University
Místo vydání
Prague
Místo konání akce
Prague
Datum konání akce
4. 8. 2019
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000558081900067