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Computation of Approximate Solutions for Guided Sampling-Based Motion Planning of 3D Objects

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00335527" target="_blank" >RIV/68407700:21230/19:00335527 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://ieeexplore.ieee.org/document/8787344" target="_blank" >https://ieeexplore.ieee.org/document/8787344</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/RoMoCo.2019.8787344" target="_blank" >10.1109/RoMoCo.2019.8787344</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Computation of Approximate Solutions for Guided Sampling-Based Motion Planning of 3D Objects

  • Popis výsledku v původním jazyce

    Motion planning of 3D solid objects leads to a search in a 6D configuration space. Sampling-based planners randomly sample the configuration space and store the collision-free samples into a graph (roadmap) that can be searched by standard graph-search methods. The well-known issue of the sampling-based planners is the narrow passage problem. Narrow passages are small collision-free regions in the configuration space that are, due to their low volume, difficult to cover by the random samples, which prevents the sampling-based planners to find a path leading through the passages. By decreasing the size of the object, the relative volume of the narrow passages is increased, which helps to cover them more densely. This allows the planner to find an approximate solution, i.e., a solution feasible for the smaller object. The approximate solution can be then used to iteratively guide the sampling in the configuration space, while increasing the size of the object, until a solution for the original object is found. In this paper, we propose a modification of the iterative guiding process. To avoid a situation where the part of the guiding path is too close to obstacles of the configuration space, we shift it away from the obstacles. This requires to estimate the surface of the obstacle region, which is achieved by detecting its boundary configurations during the sampling process. Experiments have shown that the proposed modification outperforms the simple guiding using approximate solutions, as well as other related state-of-the-art planners.

  • Název v anglickém jazyce

    Computation of Approximate Solutions for Guided Sampling-Based Motion Planning of 3D Objects

  • Popis výsledku anglicky

    Motion planning of 3D solid objects leads to a search in a 6D configuration space. Sampling-based planners randomly sample the configuration space and store the collision-free samples into a graph (roadmap) that can be searched by standard graph-search methods. The well-known issue of the sampling-based planners is the narrow passage problem. Narrow passages are small collision-free regions in the configuration space that are, due to their low volume, difficult to cover by the random samples, which prevents the sampling-based planners to find a path leading through the passages. By decreasing the size of the object, the relative volume of the narrow passages is increased, which helps to cover them more densely. This allows the planner to find an approximate solution, i.e., a solution feasible for the smaller object. The approximate solution can be then used to iteratively guide the sampling in the configuration space, while increasing the size of the object, until a solution for the original object is found. In this paper, we propose a modification of the iterative guiding process. To avoid a situation where the part of the guiding path is too close to obstacles of the configuration space, we shift it away from the obstacles. This requires to estimate the surface of the obstacle region, which is achieved by detecting its boundary configurations during the sampling process. Experiments have shown that the proposed modification outperforms the simple guiding using approximate solutions, as well as other related state-of-the-art planners.

Klasifikace

  • 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)

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/GJ19-22555Y" target="_blank" >GJ19-22555Y: Vzorkovací techniky plánování pohybu a akcí s využitím aproximačních řešení</a><br>

  • Návaznosti

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

Ostatní

  • Rok uplatnění

    2019

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    12th International Workshop on Robot Motion and Control (RoMoCo)

  • ISBN

    978-1-7281-2975-4

  • ISSN

    2575-5579

  • e-ISSN

  • Počet stran výsledku

    8

  • Strana od-do

    231-238

  • Název nakladatele

    IEEE

  • Místo vydání

    Piscataway, NJ

  • Místo konání akce

    Poznan

  • Datum konání akce

    8. 7. 2019

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    000495666000038