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Predictive and Adaptive Maps for Long-term Visual Navigation in Changing Environments

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00338343" target="_blank" >RIV/68407700:21230/19:00338343 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/IROS40897.2019.8967994" target="_blank" >https://doi.org/10.1109/IROS40897.2019.8967994</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/IROS40897.2019.8967994" target="_blank" >10.1109/IROS40897.2019.8967994</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Predictive and Adaptive Maps for Long-term Visual Navigation in Changing Environments

  • Original language description

    In this paper, we compare different map management techniques for long-term visual navigation in changing environments. In this scenario, the navigation system needs to continuously update and refine its feature map in order to adapt to the environment appearance change. To achieve reliable long-term navigation, the map management techniques have to (i) select features useful for the current navigation task, (ii) remove features that are obsolete, (iii) and add new features from the current camera view to the map. We propose several map management strategies and evaluate their performance with regard to the robot localisation accuracy in long-term teach-and-repeat navigation. Our experiments, performed over three months, indicate that strategies which model cyclic changes of the environment appearance and predict which features are going to be visible at a particular time and location, outperform strategies which do not explicitly model the temporal evolution of the changes.

  • Czech name

  • Czech description

Classification

  • 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)

Result continuities

  • 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)

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

  • ISBN

    978-1-7281-4004-9

  • ISSN

    2153-0858

  • e-ISSN

    2153-0866

  • Number of pages

    7

  • Pages from-to

    7033-7039

  • Publisher name

    IEEE

  • Place of publication

    Piscataway, NJ

  • Event location

    Macau

  • Event date

    Nov 4, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article