Multisensorial robot calibration framework and toolbox

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00352664" target="_blank" >RIV/68407700:21230/21:00352664 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/21:00352664

Výsledek na webu

<a href="https://doi.org/10.1109/HUMANOIDS47582.2021.9555803" target="_blank" >https://doi.org/10.1109/HUMANOIDS47582.2021.9555803</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/HUMANOIDS47582.2021.9555803" target="_blank" >10.1109/HUMANOIDS47582.2021.9555803</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multisensorial robot calibration framework and toolbox

Popis výsledku v původním jazyce

The accuracy of robot models critically impacts their performance. With the advent of collaborative, social, or soft robots, the stiffness of the materials and the precision of the manufactured parts drops and CAD models provide a less accurate basis for the models. On the other hand, the machines often come with a rich set of powerful yet inexpensive sensors, which opens up the possibility for self-contained calibration approaches that can be performed autonomously and repeatedly by the robot. In this work, we extend the theory dealing with robot kinematic calibration by incorporating new sensory modalities (e.g., cameras on the robot, whole-body tactile sensors), calibration types, and their combinations. We provide a unified formulation that makes it possible to combine traditional approaches (external laser tracker, constraints from contact with the external environment) with self-contained calibration available to humanoid robots (self-observation, self-contact) in a single framework and single cost function. Second, we present an open source toolbox for Matlab that provides this functionality, along with additional tools for preprocessing (e.g., dataset visualization) and evaluation (e.g., observability/identifiability). We illustrate some of the possibilities of this tool through calibration of two humanoid robots (iCub, Nao) and one industrial manipulator (dual-arm setup with Yaskawa-Motoman MA1400).

Název v anglickém jazyce

Multisensorial robot calibration framework and toolbox

Popis výsledku anglicky

The accuracy of robot models critically impacts their performance. With the advent of collaborative, social, or soft robots, the stiffness of the materials and the precision of the manufactured parts drops and CAD models provide a less accurate basis for the models. On the other hand, the machines often come with a rich set of powerful yet inexpensive sensors, which opens up the possibility for self-contained calibration approaches that can be performed autonomously and repeatedly by the robot. In this work, we extend the theory dealing with robot kinematic calibration by incorporating new sensory modalities (e.g., cameras on the robot, whole-body tactile sensors), calibration types, and their combinations. We provide a unified formulation that makes it possible to combine traditional approaches (external laser tracker, constraints from contact with the external environment) with self-contained calibration available to humanoid robots (self-observation, self-contact) in a single framework and single cost function. Second, we present an open source toolbox for Matlab that provides this functionality, along with additional tools for preprocessing (e.g., dataset visualization) and evaluation (e.g., observability/identifiability). We illustrate some of the possibilities of this tool through calibration of two humanoid robots (iCub, Nao) and one industrial manipulator (dual-arm setup with Yaskawa-Motoman MA1400).

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/GX20-24186X" target="_blank" >GX20-24186X: Vědomí celého povrchu těla pro bezpečnou a přirozenou interakci: od mozku ke kolaborativním robotům</a><br>

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)

ISBN

978-1-7281-9372-4

ISSN

2164-0572

e-ISSN

2164-0580

Počet stran výsledku

8

Strana od-do

459-466

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Munich

Datum konání akce

19. 7. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000728400200054