On Close Enough Orienteering Problem with Dubins Vehicle

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00312672" target="_blank" >RIV/68407700:21230/17:00312672 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/IROS.2017.8206453" target="_blank" >http://dx.doi.org/10.1109/IROS.2017.8206453</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS.2017.8206453" target="_blank" >10.1109/IROS.2017.8206453</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On Close Enough Orienteering Problem with Dubins Vehicle

Popis výsledku v původním jazyce

In this paper, we address a generalization of the Orienteering Problem (OP) for curvature-constrained vehicles and to problems where it is allowed to collect a reward associated to each target location within a specified distance from the target. The addressed problem combines challenges of the combinatorial optimization of the OP (to select the most rewarding targets and find the optimal sequence to visit them) with the continuous optimization related to the determination of the waypoint locations and suitable headings at the waypoints for the considered Dubins vehicle such that the curvature-constrained path does not exceed the given travel budget and the sum of the collected rewards is maximized. The proposed generalization is called the Close Enough Dubins Orienteering Problem (CEDOP) and novel unsupervised learning approach is proposed to address computational requirements of this challenging planning problem. Based on the presented results, the proposed approach is feasible and provides a bit worse solution of CEDOP than the existing combinatorial approach but with significantly lower computational requirements.

Název v anglickém jazyce

On Close Enough Orienteering Problem with Dubins Vehicle

Popis výsledku anglicky

In this paper, we address a generalization of the Orienteering Problem (OP) for curvature-constrained vehicles and to problems where it is allowed to collect a reward associated to each target location within a specified distance from the target. The addressed problem combines challenges of the combinatorial optimization of the OP (to select the most rewarding targets and find the optimal sequence to visit them) with the continuous optimization related to the determination of the waypoint locations and suitable headings at the waypoints for the considered Dubins vehicle such that the curvature-constrained path does not exceed the given travel budget and the sum of the collected rewards is maximized. The proposed generalization is called the Close Enough Dubins Orienteering Problem (CEDOP) and novel unsupervised learning approach is proposed to address computational requirements of this challenging planning problem. Based on the presented results, the proposed approach is feasible and provides a bit worse solution of CEDOP than the existing combinatorial approach but with significantly lower computational requirements.

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

<a href="/cs/project/GA16-24206S" target="_blank" >GA16-24206S: Metody informatického plánování cest pro neholonomní mobilní roboty v úlohách monitorování a dohledu</a><br>

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

ISBN

978-1-5386-2682-5

ISSN

2153-0858

e-ISSN

—

Počet stran výsledku

7

Strana od-do

5646-5652

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Vancouver

Datum konání akce

24. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000426978205047