Tracked Robot Odometry for Obstacle Traversal in Sensory Deprived Environment

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00336122" target="_blank" >RIV/68407700:21230/19:00336122 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/19:00336122

Výsledek na webu

<a href="https://doi.org/10.1109/TMECH.2019.2945031" target="_blank" >https://doi.org/10.1109/TMECH.2019.2945031</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TMECH.2019.2945031" target="_blank" >10.1109/TMECH.2019.2945031</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Tracked Robot Odometry for Obstacle Traversal in Sensory Deprived Environment

Popis výsledku v původním jazyce

Mobile-tracked robots are suitable for traversing rough terrain. However, standard exteroceptive localization methods (visual or laser SLAM) may be unreliable due to smoke, dust, fog, or insufficient lighting in harsh conditions of urban search and rescue missions. During extensive end-user evaluations in real-world conditions of such scenarios, we have observed that the accuracy of dead-reckoning localization suffers while traversing vertical obstacles. We propose to combine explicit modeling of robot kinematics and data-driven approach based on machine learning. The proposed method is experimentally verified indoors and outdoors traversing various obstacles. Indoors, a reference position has been recorded as well to assess the accuracy of our solution. The experimental dataset is released to the public to help the robotics community.

Název v anglickém jazyce

Tracked Robot Odometry for Obstacle Traversal in Sensory Deprived Environment

Popis výsledku anglicky

Mobile-tracked robots are suitable for traversing rough terrain. However, standard exteroceptive localization methods (visual or laser SLAM) may be unreliable due to smoke, dust, fog, or insufficient lighting in harsh conditions of urban search and rescue missions. During extensive end-user evaluations in real-world conditions of such scenarios, we have observed that the accuracy of dead-reckoning localization suffers while traversing vertical obstacles. We propose to combine explicit modeling of robot kinematics and data-driven approach based on machine learning. The proposed method is experimentally verified indoors and outdoors traversing various obstacles. Indoors, a reference position has been recorded as well to assess the accuracy of our solution. The experimental dataset is released to the public to help the robotics community.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

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

2019

Kód důvěrnosti údajů

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

Název periodika

IEEE-ASME TRANSACTIONS ON MECHATRONICS

ISSN

1083-4435

e-ISSN

1941-014X

Svazek periodika

24

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

11

Strana od-do

2745-2755

Kód UT WoS článku

000506621800029

EID výsledku v databázi Scopus

2-s2.0-85077814262