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Traversability Transfer Learning Between Robots with Different Cost Assessment Policies

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00359490" target="_blank" >RIV/68407700:21230/22:00359490 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-030-98260-7_21" target="_blank" >https://doi.org/10.1007/978-3-030-98260-7_21</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-98260-7_21" target="_blank" >10.1007/978-3-030-98260-7_21</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Traversability Transfer Learning Between Robots with Different Cost Assessment Policies

  • Original language description

    Predicting mobile robots' traversability over terrains is crucial to select safe and efficient paths through rough and unstructured environments. In multi-robot missions, knowledge transfer techniques can enable learning terrain traversability assessment the robots did not experience individually. The knowledge can be incrementally aggregated for homogeneous robots since they can treat foreign knowledge as their own. However, robots with different perceptions might experience the same terrain differently, so it is impossible to aggregate the shared knowledge directly. In this paper, we show how to learn a model that transfers the experience between heterogeneous robots, enabling each robot to use the whole sum of the experience of the multi-robot team. The proposed approach uses correlation to combine individual neural networks that assess the traversability of individual robots. The presented method has been verified in a real-world deployment of multi-legged walking robots with different cost assessment policies.

  • 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

    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

    2022

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Modelling and Simulation for Autonomus Systems

  • ISBN

    978-3-030-98259-1

  • ISSN

    0302-9743

  • e-ISSN

    1611-3349

  • Number of pages

    12

  • Pages from-to

    333-344

  • Publisher name

    Springer-Verlag

  • Place of publication

    Berlin

  • Event location

    Virtual

  • Event date

    Oct 20, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000787774900021