Dead reckoning in a dynamic quadruped robot: inertial navigation system aided by a legged odometer

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00183150" target="_blank" >RIV/68407700:21230/11:00183150 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICRA.2011.5979609" target="_blank" >http://dx.doi.org/10.1109/ICRA.2011.5979609</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICRA.2011.5979609" target="_blank" >10.1109/ICRA.2011.5979609</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Dead reckoning in a dynamic quadruped robot: inertial navigation system aided by a legged odometer

Popis výsledku v původním jazyce

The information bout posture and to gauge the distance it travelled can be obtained from various sources. In this work, we have addressed this problem in a dynamic quadruped robot. We have designed and implemented a navigation algorithm for full body state estimation that does not use any external reference . Extended Kalman Filter was used to provide error estimation and data fusion from two independent sources of information: Inertial Navigation System mechanization algorithm processing raw inertial data, and legged odometry, which provided velocity aiding. We present a novel data-driven architecture for legged odometry that relies on a combination of joint sensor signals and pressure sensors. Our navigation system ensures precise tracking of a running robot's posture (roll and pitch), and satisfactory tracking of its position over medium time intervals. We have shown our method to work for two different dynamic turning gaits and on two terrains with significantly different friction.

Název v anglickém jazyce

Dead reckoning in a dynamic quadruped robot: inertial navigation system aided by a legged odometer

Popis výsledku anglicky

The information bout posture and to gauge the distance it travelled can be obtained from various sources. In this work, we have addressed this problem in a dynamic quadruped robot. We have designed and implemented a navigation algorithm for full body state estimation that does not use any external reference . Extended Kalman Filter was used to provide error estimation and data fusion from two independent sources of information: Inertial Navigation System mechanization algorithm processing raw inertial data, and legged odometry, which provided velocity aiding. We present a novel data-driven architecture for legged odometry that relies on a combination of joint sensor signals and pressure sensors. Our navigation system ensures precise tracking of a running robot's posture (roll and pitch), and satisfactory tracking of its position over medium time intervals. We have shown our method to work for two different dynamic turning gaits and on two terrains with significantly different friction.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/GD102%2F09%2FH082" target="_blank" >GD102/09/H082: Senzory a inteligentní senzorové systémy</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

ICRA2011: Proceedings of 2011 IEEE International Conference on Robotics and Automation

ISBN

978-1-61284-386-5

ISSN

1050-4729

e-ISSN

—

Počet stran výsledku

8

Strana od-do

617-624

Název nakladatele

Omnipress

Místo vydání

Madison

Místo konání akce

Shanghai

Datum konání akce

9. 5. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000295396600097