All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Warped Hypertime Representations for Long-term Autonomy of Mobile Robots

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332172" target="_blank" >RIV/68407700:21230/19:00332172 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/LRA.2019.2926682" target="_blank" >https://doi.org/10.1109/LRA.2019.2926682</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/LRA.2019.2926682" target="_blank" >10.1109/LRA.2019.2926682</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Warped Hypertime Representations for Long-term Autonomy of Mobile Robots

  • Original language description

    This paper presents a novel method for introducing time into discrete and continuous spatial representations used in mobile robotics, by modelling long-term, pseudo-periodic variations caused by human activities or natural processes. Unlike previous approaches, the proposed method does not treat time and space separately, and its continuous nature respects both the temporal and spatial continuity of the modeled phenomena. The key idea is to extend the spatial model with a set of wrapped time dimensions that represent the periodicities of the observed events. By performing clustering over this extended representation, we obtain a model that allows the prediction of probabilistic distributions of future states and events in both discrete and continuous spatial representations. We apply the proposed algorithm to several long-term datasets acquired by mobile robots and show that the method enables a robot to predict future states of representations with different dimensions. The experiments further show that the method achieves more accurate predictions than the previous state of the art.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

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

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    IEEE Robotics and Automation Letters

  • ISSN

    2377-3766

  • e-ISSN

    2377-3766

  • Volume of the periodical

    4

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    8

  • Pages from-to

    3310-3317

  • UT code for WoS article

    000476791300026

  • EID of the result in the Scopus database

    2-s2.0-85069761513