LTL Robot Motion Control based on Automata Learning of Environmental Dynamics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F12%3A00057680" target="_blank" >RIV/00216224:14330/12:00057680 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICRA.2012.6225075" target="_blank" >http://dx.doi.org/10.1109/ICRA.2012.6225075</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICRA.2012.6225075" target="_blank" >10.1109/ICRA.2012.6225075</a>

Jazyk výsledku

angličtina

Název v původním jazyce

LTL Robot Motion Control based on Automata Learning of Environmental Dynamics

Popis výsledku v původním jazyce

We develop a technique to automatically generate a control policy for a robot moving in an environment that includes elements with partially unknown, changing behavior. The robot is required to achieve an optimal surveillance mission, in which a certainrequest needs to be serviced repeatedly, while the expected time in between consecutive services is minimized. We define a fragment of Linear Temporal Logic (LTL) to describe such a mission and formulate the problem as a temporal logic game. Our approachis based on two main ideas. First, we extend results in automata learning to detect patterns of the partially unknown behavior of the elements in the environment. Second, we employ an automata-theoretic method to generate the control policy. We show that the obtained control policy converges to an optimal one when the unknown behavior patterns are fully learned. We implemented the proposed computational framework in MATLAB. Illustrative case studies are included.

Název v anglickém jazyce

LTL Robot Motion Control based on Automata Learning of Environmental Dynamics

Popis výsledku anglicky

We develop a technique to automatically generate a control policy for a robot moving in an environment that includes elements with partially unknown, changing behavior. The robot is required to achieve an optimal surveillance mission, in which a certainrequest needs to be serviced repeatedly, while the expected time in between consecutive services is minimized. We define a fragment of Linear Temporal Logic (LTL) to describe such a mission and formulate the problem as a temporal logic game. Our approachis based on two main ideas. First, we extend results in automata learning to detect patterns of the partially unknown behavior of the elements in the environment. Second, we employ an automata-theoretic method to generate the control policy. We show that the obtained control policy converges to an optimal one when the unknown behavior patterns are fully learned. We implemented the proposed computational framework in MATLAB. Illustrative case studies are included.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název statě ve sborníku

2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)

ISBN

9781467314053

ISSN

1050-4729

e-ISSN

—

Počet stran výsledku

6

Strana od-do

5177-5182

Název nakladatele

IEEE

Místo vydání

NEW YORK

Místo konání akce

St Paul, MN

Datum konání akce

14. 5. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000309406705032