Performance Comparison of Visual Teach and Repeat Systems for Mobile Robots

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00366932" target="_blank" >RIV/68407700:21230/23:00366932 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-031-31268-7_1" target="_blank" >https://doi.org/10.1007/978-3-031-31268-7_1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-31268-7_1" target="_blank" >10.1007/978-3-031-31268-7_1</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Performance Comparison of Visual Teach and Repeat Systems for Mobile Robots

Popis výsledku v původním jazyce

In practical work scenarios, it is often necessary to repeat specific tasks, which include navigating along a desired path. Visual teach and repeat systems are a type of autonomous navigation in which a robot repeats a previously taught path using a camera and dead reckoning. There have been many different teach and repeat methods proposed in the literature, but only a few are open-source. In this paper, we compare four recently published open-source methods and a Boston Dynamics proprietary solution embedded in a Spot robot. The intended use for each method is different, which has an impact on their strengths and weaknesses. When deciding which method to use, factors such as the environment and desired precision and speed should be taken into consideration. For example, in controlled artificial environments, which do not change significantly, navigation precision and speed are more important than robustness to environment variations. However, the appearance of unstructured natural environments varies over time, making robustness to changes a crucial property for outdoor navigation systems. This paper compares the speed, precision, reliability, robustness, and practicality of the available teach and repeat methods. We will outline their flaws and strengths, helping to choose the most suitable method for a particular utilization.

Název v anglickém jazyce

Performance Comparison of Visual Teach and Repeat Systems for Mobile Robots

Popis výsledku anglicky

In practical work scenarios, it is often necessary to repeat specific tasks, which include navigating along a desired path. Visual teach and repeat systems are a type of autonomous navigation in which a robot repeats a previously taught path using a camera and dead reckoning. There have been many different teach and repeat methods proposed in the literature, but only a few are open-source. In this paper, we compare four recently published open-source methods and a Boston Dynamics proprietary solution embedded in a Spot robot. The intended use for each method is different, which has an impact on their strengths and weaknesses. When deciding which method to use, factors such as the environment and desired precision and speed should be taken into consideration. For example, in controlled artificial environments, which do not change significantly, navigation precision and speed are more important than robustness to environment variations. However, the appearance of unstructured natural environments varies over time, making robustness to changes a crucial property for outdoor navigation systems. This paper compares the speed, precision, reliability, robustness, and practicality of the available teach and repeat methods. We will outline their flaws and strengths, helping to choose the most suitable method for a particular utilization.

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/GC20-27034J" target="_blank" >GC20-27034J: Rozšíření prostorových modelů explicitní representací času pro dlouhodobou autonomii mobilních robotů</a><br>

Návaznosti

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

Rok uplatnění

2023

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 2022)

ISBN

978-3-031-31267-0

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

22

Strana od-do

3-24

Název nakladatele

Springer, Cham

Místo vydání

—

Místo konání akce

Praha

Datum konání akce

20. 10. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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