A Versatile Visual Navigation System for Autonomous Vehicles

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332097" target="_blank" >RIV/68407700:21230/19:00332097 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/content/pdf/10.1007%2F978-3-030-14984-0.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007%2F978-3-030-14984-0.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-14984-0_8" target="_blank" >10.1007/978-3-030-14984-0_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Versatile Visual Navigation System for Autonomous Vehicles

Popis výsledku v původním jazyce

We present a universal visual navigation method which allows a vehicle to autonomously repeat paths previously taught by a human operator. The method is computationally efficient and does not require camera calibration. It can learn and autonomously traverse arbitrarily shaped paths and is robust to appearance changes induced by varying outdoor illumination and naturally-occurring environment changes. The method does not perform explicit position estimation in the 2d/3d space, but it relies on a novel mathematical theorem, which allows fusing exteroceptive and interoceptive sensory data in a way that ensures navigation accuracy and reliability. The experiments performed indicate that the proposed navigation method can accurately guide different autonomous vehicles along the desired path. The presented system, which was already deployed in patrolling scenarios, is provided as open source at www.github.com/gestom/stroll_bearnav.

Název v anglickém jazyce

A Versatile Visual Navigation System for Autonomous Vehicles

Popis výsledku anglicky

We present a universal visual navigation method which allows a vehicle to autonomously repeat paths previously taught by a human operator. The method is computationally efficient and does not require camera calibration. It can learn and autonomously traverse arbitrarily shaped paths and is robust to appearance changes induced by varying outdoor illumination and naturally-occurring environment changes. The method does not perform explicit position estimation in the 2d/3d space, but it relies on a novel mathematical theorem, which allows fusing exteroceptive and interoceptive sensory data in a way that ensures navigation accuracy and reliability. The experiments performed indicate that the proposed navigation method can accurately guide different autonomous vehicles along the desired path. The presented system, which was already deployed in patrolling scenarios, is provided as open source at www.github.com/gestom/stroll_bearnav.

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/GJ17-27006Y" target="_blank" >GJ17-27006Y: Prostorově temporální representace pro dlouhodobou navigaci mobilních robotů</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 (MESAS 2018)

ISBN

978-3-030-14983-3

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

21

Strana od-do

90-110

Název nakladatele

Springer International Publishing AG

Místo vydání

Cham

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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