Modelling and predicting rhythmic flow patterns in dynamic environments

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00323924" target="_blank" >RIV/68407700:21230/18:00323924 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/chapter/10.1007/978-3-319-96728-8_12" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-96728-8_12</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-96728-8_12" target="_blank" >10.1007/978-3-319-96728-8_12</a>

Jazyk výsledku
angličtina
Název v původním jazyce
Modelling and predicting rhythmic flow patterns in dynamic environments
Popis výsledku v původním jazyce
We present a time-dependent probabilistic map able to model and predict flow patterns of people in indoor environments. The proposed representation models the likelihood of motion direction on a grid-based map by a set of harmonic functions, which efficiently capture long-term (minutes to weeks) variations of crowd movements over time. The evaluation, performed on data from two real environments, shows that the proposed model enables prediction of human movement patterns in the future. Potential applications include human-aware motion planning, improving the efficiency and safety of robot navigation.
Název v anglickém jazyce
Modelling and predicting rhythmic flow patterns in dynamic environments
Popis výsledku anglicky
We present a time-dependent probabilistic map able to model and predict flow patterns of people in indoor environments. The proposed representation models the likelihood of motion direction on a grid-based map by a set of harmonic functions, which efficiently capture long-term (minutes to weeks) variations of crowd movements over time. The evaluation, performed on data from two real environments, shows that the proposed model enables prediction of human movement patterns in the future. Potential applications include human-aware motion planning, improving the efficiency and safety of robot navigation.

Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt
<a href="/cs/project/GJ17-27006Y" target="_blank" >GJ17-27006Y: Prostorově temporální representace pro dlouhodobou navigaci mobilních robotů</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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