Modelling and predicting rhythmic flow patterns in dynamic environments

Result code in 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>
Result on the web
<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>

Result language
angličtina
Original language name
Modelling and predicting rhythmic flow patterns in dynamic environments
Original language description
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.
Czech name
—
Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GJ17-27006Y" target="_blank" >GJ17-27006Y: Spatio-temporal representations for life-long mobile robot navigation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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