Incremental Learning of Traversability Cost for Aerial Reconnaissance Support to Ground Units

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332827" target="_blank" >RIV/68407700:21230/19:00332827 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-14984-0_30" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-14984-0_30</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-14984-0_30" target="_blank" >10.1007/978-3-030-14984-0_30</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Incremental Learning of Traversability Cost for Aerial Reconnaissance Support to Ground Units

Popis výsledku v původním jazyce

In this paper, we address traversability cost estimation using exteroceptive and proprioceptive data collected by a team of aerial and ground vehicles. The main idea of the proposed approach is to estimate the terrain traversability cost based on the real experience of the multi-legged walking robot with traversing different terrain types. We propose to combine visual features with the real measured traversability cost based on proprioceptive signals of the utilized hexapod walking robot as a ground unit. The estimated traversability cost is augmented by extracted visual features from the onboard robot camera, and the features are utilized to extrapolate the learned traversability model for an aerial scan of new environments to assess their traversability cost. The extrapolated traversability cost can be utilized in the high-level mission planning to avoid areas that are difficult to traverse but not visited by the ground units. The proposed approach has been experimentally verified with a real hexapod walking robot in indoor and outdoor scenarios.

Název v anglickém jazyce

Incremental Learning of Traversability Cost for Aerial Reconnaissance Support to Ground Units

Popis výsledku anglicky

In this paper, we address traversability cost estimation using exteroceptive and proprioceptive data collected by a team of aerial and ground vehicles. The main idea of the proposed approach is to estimate the terrain traversability cost based on the real experience of the multi-legged walking robot with traversing different terrain types. We propose to combine visual features with the real measured traversability cost based on proprioceptive signals of the utilized hexapod walking robot as a ground unit. The estimated traversability cost is augmented by extracted visual features from the onboard robot camera, and the features are utilized to extrapolate the learned traversability model for an aerial scan of new environments to assess their traversability cost. The extrapolated traversability cost can be utilized in the high-level mission planning to avoid areas that are difficult to traverse but not visited by the ground units. The proposed approach has been experimentally verified with a real hexapod walking robot in indoor and outdoor scenarios.

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/GA18-18858S" target="_blank" >GA18-18858S: Metody kontinuálního učení řízení pohybu vícenohých kráčejích robotů v úlohách autonomního sběru dat</a><br>

Návaznosti

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

Rok uplatnění

2019

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

978-3-030-14983-3

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

10

Strana od-do

412-421

Název nakladatele

Springer

Místo vydání

Basel

Místo konání akce

Praha

Datum konání akce

17. 10. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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