Computing multiple guiding paths for sampling-based motion planning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00335548" target="_blank" >RIV/68407700:21230/19:00335548 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14330/19:00107686

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICAR46387.2019.8981589" target="_blank" >http://dx.doi.org/10.1109/ICAR46387.2019.8981589</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICAR46387.2019.8981589" target="_blank" >10.1109/ICAR46387.2019.8981589</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Computing multiple guiding paths for sampling-based motion planning

Popis výsledku v původním jazyce

Path planning of 3D solid objects leads to search in a six-dimensional configuration space, which can be solved by sampling-based motion planning. The well-known issue of sampling-based planners is the narrow passage problem, which is caused by the presence of small regions of the configuration space that are difficult to cover by random samples. Guided-based planners cope with this issue by increasing the probability of sampling along an estimated solution (a guiding path). In the case of six-dimensional configuration space, the guiding path needs to be computed in the configuration space rather than in the workspace. Fast computation of guiding paths can be achieved by solving a similar, yet simpler problem, e.g., by reducing the size of the robot. This results in an approximate solution (path) that is assumed to be located near the solution of the original problem. The guided sampling along this approximate solution may, however, fail if the approximate solution is too far from the desired solution. In this paper, we cope with this problem by sampling the configuration space along multiple approximate solutions. The approximate solutions are computed using a proposed iterative process: after a path (solution) is found, it forms a region where the subsequent search is inhibited, which boosts the search of new solutions. The performance of the proposed approach is verified in scenarios with multiple narrow passages and compared with the state-of-the-art planners.

Název v anglickém jazyce

Computing multiple guiding paths for sampling-based motion planning

Popis výsledku anglicky

Path planning of 3D solid objects leads to search in a six-dimensional configuration space, which can be solved by sampling-based motion planning. The well-known issue of sampling-based planners is the narrow passage problem, which is caused by the presence of small regions of the configuration space that are difficult to cover by random samples. Guided-based planners cope with this issue by increasing the probability of sampling along an estimated solution (a guiding path). In the case of six-dimensional configuration space, the guiding path needs to be computed in the configuration space rather than in the workspace. Fast computation of guiding paths can be achieved by solving a similar, yet simpler problem, e.g., by reducing the size of the robot. This results in an approximate solution (path) that is assumed to be located near the solution of the original problem. The guided sampling along this approximate solution may, however, fail if the approximate solution is too far from the desired solution. In this paper, we cope with this problem by sampling the configuration space along multiple approximate solutions. The approximate solutions are computed using a proposed iterative process: after a path (solution) is found, it forms a region where the subsequent search is inhibited, which boosts the search of new solutions. The performance of the proposed approach is verified in scenarios with multiple narrow passages and compared with the state-of-the-art planners.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/GA17-07690S" target="_blank" >GA17-07690S: Metody identifikace a vizualizace tunelů pro flexibilní ligandy v dynamických proteinech</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

ICAR2019: Proceedings of the 19th International Conference on Advanced Robotics

ISBN

978-1-7281-2467-4

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

374-381

Název nakladatele

IEEE

Místo vydání

Piscataway (New Jersey)

Místo konání akce

Belo Horizonte

Datum konání akce

2. 12. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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