Unifying multi-goal path planning for autonomous data collection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00225362" target="_blank" >RIV/68407700:21230/14:00225362 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/IROS.2014.6942967" target="_blank" >http://dx.doi.org/10.1109/IROS.2014.6942967</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS.2014.6942967" target="_blank" >10.1109/IROS.2014.6942967</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Unifying multi-goal path planning for autonomous data collection

Popis výsledku v původním jazyce

In this paper, we propose a framework for solving variants of the multi-goal path planning problem with applications to autonomous data collection. Autonomous data collection requires optimizing the trajectory of a mobile vehicle to collect data from a number of stationary sensors in a known configuration. The proposed approach utilizes the self-organizing map (SOM) architecture to provide a unified solution to multi-goal path planning problems. Our approach applies to cases where the vehicle must movewithin a radius of a sensor to collect data and also where some sensors can be ignored due to a lower priority. We compare our proposed approach to state-of-the-art approximate solutions to variants of the Traveling Salesman Problem (TSP) for random deployments and in an underwater monitoring application domain. Our results demonstrate that the SOM approach outperforms combinatorial heuristic algorithms and also provides a unified approach for solving variants of the multi-goal path plan

Název v anglickém jazyce

Unifying multi-goal path planning for autonomous data collection

Popis výsledku anglicky

In this paper, we propose a framework for solving variants of the multi-goal path planning problem with applications to autonomous data collection. Autonomous data collection requires optimizing the trajectory of a mobile vehicle to collect data from a number of stationary sensors in a known configuration. The proposed approach utilizes the self-organizing map (SOM) architecture to provide a unified solution to multi-goal path planning problems. Our approach applies to cases where the vehicle must movewithin a radius of a sensor to collect data and also where some sensors can be ignored due to a lower priority. We compare our proposed approach to state-of-the-art approximate solutions to variants of the Traveling Salesman Problem (TSP) for random deployments and in an underwater monitoring application domain. Our results demonstrate that the SOM approach outperforms combinatorial heuristic algorithms and also provides a unified approach for solving variants of the multi-goal path plan

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

<a href="/cs/project/GP13-18316P" target="_blank" >GP13-18316P: Samo-organizující se sítě v robotických úlohách plánování cesty přes více cílů</a><br>

Návaznosti

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

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems

ISBN

978-1-4799-6934-0

ISSN

2153-0858

e-ISSN

—

Počet stran výsledku

6

Strana od-do

2937-2942

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Chicago

Datum konání akce

14. 9. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—