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PROBABILITY LINEAR METHOD POINT CLOUD APPROXIMATION

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F20%3APU138432" target="_blank" >RIV/00216305:26210/20:PU138432 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.engmech.cz/im/im/download/EM2020_proceedings.pdf" target="_blank" >https://www.engmech.cz/im/im/download/EM2020_proceedings.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.21495/5896-3-306" target="_blank" >10.21495/5896-3-306</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    PROBABILITY LINEAR METHOD POINT CLOUD APPROXIMATION

  • Original language description

    Fitting curves through point clouds is useful when the further computation is required to be fast or the data set is too large. The most common method to fit a curve into a point cloud is the approximation using the Least squares method (LSM) but it can be used only when the expected data have normal distribution. Data obtained from LIDAR often tend to have an error which can’t be solved by LSM, like data shifted in one angular direction. The main goal of this paper is to propose more efficient method for estimation of obstacle position and orientation. This method uses curve approximation based on probability; this can solve some classic errors that appear when processing data obtained by LIDAR. This method was tested and was found to have a disadvantage: great demand for computing power; its more than ten times slower than classic LSM and in cases with normal distribution gives the same results. It can be used in system where the emphasis is on accuracy or in multiagent solution when working with big data set is not desired.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    ENGINEERING MECHANICS 2020 26th INTERNATIONAL CONFERENCE

  • ISBN

    978-80-214-5896-3

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    306-309

  • Publisher name

    Neuveden

  • Place of publication

    neuveden

  • Event location

    Online

  • Event date

    Nov 24, 2020

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article

    000667956100069