Spatio-temporal Representation for Long-term Anticipation of Human Presence in Service Robotics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00334742" target="_blank" >RIV/68407700:21230/19:00334742 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/8793534" target="_blank" >https://ieeexplore.ieee.org/document/8793534</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICRA.2019.8793534" target="_blank" >10.1109/ICRA.2019.8793534</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Spatio-temporal Representation for Long-term Anticipation of Human Presence in Service Robotics

Popis výsledku v původním jazyce

We propose an efficient spatio-temporal model for mobile autonomous robots operating in human populated environments. Our method aims to model periodic temporal patterns of people presence, which are based on peoples' routines and habits. The core idea is to project the time onto a set of wrapped dimensions that represent the periodicities of people presence. Extending a 2D spatial model with this multidimensional representation of time results in a memory efficient spatio-temporal model. This model is capable of long-term predictions of human presence, allowing mobile robots to schedule their services better and to plan their paths. The experimental evaluation, performed over datasets gathered by a robot over a period of several weeks, indicates that the proposed method achieves more accurate predictions than the previous state of the art used in robotics.

Název v anglickém jazyce

Spatio-temporal Representation for Long-term Anticipation of Human Presence in Service Robotics

Popis výsledku anglicky

We propose an efficient spatio-temporal model for mobile autonomous robots operating in human populated environments. Our method aims to model periodic temporal patterns of people presence, which are based on peoples' routines and habits. The core idea is to project the time onto a set of wrapped dimensions that represent the periodicities of people presence. Extending a 2D spatial model with this multidimensional representation of time results in a memory efficient spatio-temporal model. This model is capable of long-term predictions of human presence, allowing mobile robots to schedule their services better and to plan their paths. The experimental evaluation, performed over datasets gathered by a robot over a period of several weeks, indicates that the proposed method achieves more accurate predictions than the previous state of the art used in robotics.

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

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of 2019 International Conference on Robotics and Automation

ISBN

978-1-5386-6026-3

ISSN

1050-4729

e-ISSN

2577-087X

Počet stran výsledku

7

Strana od-do

2620-2626

Název nakladatele

IEEE Xplore

Místo vydání

—

Místo konání akce

Montreal

Datum konání akce

20. 5. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000494942301144