Simulation-Based Goal-Selection for Autonomous Exploration

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00225215" target="_blank" >RIV/68407700:21230/14:00225215 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Simulation-Based Goal-Selection for Autonomous Exploration

Popis výsledku v původním jazyce

High-level planning can be defined as the process of selection of an appropriate solution from a set of possible candidates. This process typically evaluates each candidate according to some reward function consisting of (1) cost, i.e., effort needed toaccomplish the candidate and (2) the utility of accomplishing it and then selects the best one according to this evaluation.The key problem lies in the fact that the reward function can be rarely evaluated precisely. At the example of the problem of exploration of an unknown environment by a modular robot we show that precise simulation-based estimation of the cost function leads to better decisions of high-level planning and thus improves exploration process performance. State-of-the-art techniques compute the cost function in goal-selection as a length of the path from the current robot position to a goal-candidate. This is sufficient for robots with simple kinematics for which time to reach a candidate highly correlates with a path l

Název v anglickém jazyce

Simulation-Based Goal-Selection for Autonomous Exploration

Popis výsledku anglicky

High-level planning can be defined as the process of selection of an appropriate solution from a set of possible candidates. This process typically evaluates each candidate according to some reward function consisting of (1) cost, i.e., effort needed toaccomplish the candidate and (2) the utility of accomplishing it and then selects the best one according to this evaluation.The key problem lies in the fact that the reward function can be rarely evaluated precisely. At the example of the problem of exploration of an unknown environment by a modular robot we show that precise simulation-based estimation of the cost function leads to better decisions of high-level planning and thus improves exploration process performance. State-of-the-art techniques compute the cost function in goal-selection as a length of the path from the current robot position to a goal-candidate. This is sufficient for robots with simple kinematics for which time to reach a candidate highly correlates with a path l

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

<a href="/cs/project/TE01020197" target="_blank" >TE01020197: Centrum aplikované kybernetiky 3</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

Modelling and Simulation for Autonomous Systems

ISBN

978-3-319-13822-0

ISSN

0302-9743

e-ISSN

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Počet stran výsledku

11

Strana od-do

173-183

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Rome

Datum konání akce

5. 5. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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