Iterative Solution for the Narrow Passage Problem in Motion Planning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43966432" target="_blank" >RIV/49777513:23520/22:43966432 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-031-08751-6_16" target="_blank" >http://dx.doi.org/10.1007/978-3-031-08751-6_16</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-08751-6_16" target="_blank" >10.1007/978-3-031-08751-6_16</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Iterative Solution for the Narrow Passage Problem in Motion Planning

Popis výsledku v původním jazyce

Finding a path in a narrow passage is a bottleneck for randomised sampling-based motion planning methods. This paper introduces a technique that solves this problem. The main inspiration was the method of exit areas for cavities in protein models, but the proposed solution can also be used in another context. For data with narrow passages, the proposed method finds passageways for which sampling-based methods are not sufficient, or provides information that a collision-free path does not exist. With such information, it is possible to quit the motion planning computation if no solution exists and its further search would be a loss of time. Otherwise, the method continues to sample the space with sampling-based method (a RRT algorithm) until a solution is found or the maximum number of iterations is reached. The method was tested on real biomolecular data - dcp protein - and on artificial data (to show the superiority of the proposed solution on better-imagined data) with positive results.

Název v anglickém jazyce

Iterative Solution for the Narrow Passage Problem in Motion Planning

Popis výsledku anglicky

Finding a path in a narrow passage is a bottleneck for randomised sampling-based motion planning methods. This paper introduces a technique that solves this problem. The main inspiration was the method of exit areas for cavities in protein models, but the proposed solution can also be used in another context. For data with narrow passages, the proposed method finds passageways for which sampling-based methods are not sufficient, or provides information that a collision-free path does not exist. With such information, it is possible to quit the motion planning computation if no solution exists and its further search would be a loss of time. Otherwise, the method continues to sample the space with sampling-based method (a RRT algorithm) until a solution is found or the maximum number of iterations is reached. The method was tested on real biomolecular data - dcp protein - and on artificial data (to show the superiority of the proposed solution on better-imagined data) with positive results.

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)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Computer Science 22nd International Conference on Computational Science, ICCS 2022

ISBN

978-3-031-08750-9

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

14

Strana od-do

219-232

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

London

Datum konání akce

21. 6. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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