Precise Positioning and Heading for Autonomous Scouting Robots in a Harsh Environment

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F19%3A43915743" target="_blank" >RIV/62156489:43210/19:43915743 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-19651-6_9" target="_blank" >https://doi.org/10.1007/978-3-030-19651-6_9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-19651-6_9" target="_blank" >10.1007/978-3-030-19651-6_9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Precise Positioning and Heading for Autonomous Scouting Robots in a Harsh Environment

Popis výsledku v původním jazyce

This document describes the design and verification of the GreenPatrol localization subsystem. Greenpatrol is an autonomous robot system intended to operate in light indoor environments, such as greenhouses, detecting and treating pests in high-value crops such as tomato and pepper. High accuracy positioning is required for performing this in a trustable and safety manner. The proposed localization solution is described hereafter. Test have been carried out in the real greenhouse environment. The proposed localization subsystem consists of two differentiate parts: (1) an absolute localization module which uses precise positioning GNSS techniques in combination with the robot proprioceptive sensors (i.e. inertial sensors and odometry) with an estimated position error lower than 30 cm, and (2) a relative localization module that takes the absolute solution as input and combines it with the robot range readings to generate a model of the environment and to estimate the robot position and heading inside it. From the analysis of the tests results it follows that the absolute localization is able to provide a heading solution with accuracy 5. more than a 85% of the time. The relative localization algorithm, on the other hand, gives an estimation of the robot position inside the map which does not improve significantly the absolute solution, but it is able to refine the heading estimation and to absorb transitory error peaks. This paper is organized as follows: first an introduction describing the robot localization system purposed and the state of the art of the involved technologies, second a description of the main subsystems involved and the problems associated, then the tests carried out in a real scenario and the obtained results for check its behavior for each one of the subsystems, and finally conclusions and future work.

Název v anglickém jazyce

Precise Positioning and Heading for Autonomous Scouting Robots in a Harsh Environment

Popis výsledku anglicky

This document describes the design and verification of the GreenPatrol localization subsystem. Greenpatrol is an autonomous robot system intended to operate in light indoor environments, such as greenhouses, detecting and treating pests in high-value crops such as tomato and pepper. High accuracy positioning is required for performing this in a trustable and safety manner. The proposed localization solution is described hereafter. Test have been carried out in the real greenhouse environment. The proposed localization subsystem consists of two differentiate parts: (1) an absolute localization module which uses precise positioning GNSS techniques in combination with the robot proprioceptive sensors (i.e. inertial sensors and odometry) with an estimated position error lower than 30 cm, and (2) a relative localization module that takes the absolute solution as input and combines it with the robot range readings to generate a model of the environment and to estimate the robot position and heading inside it. From the analysis of the tests results it follows that the absolute localization is able to provide a heading solution with accuracy 5. more than a 85% of the time. The relative localization algorithm, on the other hand, gives an estimation of the robot position inside the map which does not improve significantly the absolute solution, but it is able to refine the heading estimation and to absorb transitory error peaks. This paper is organized as follows: first an introduction describing the robot localization system purposed and the state of the art of the involved technologies, second a description of the main subsystems involved and the problems associated, then the tests carried out in a real scenario and the obtained results for check its behavior for each one of the subsystems, and finally conclusions and future work.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

O - Projekt operacniho programu

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

From Bioinspired Systems and Biomedical Applications to Machine Learning. Part II

ISBN

978-3-030-19650-9

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

15

Strana od-do

82-96

Název nakladatele

Springer Switzerland

Místo vydání

Cham

Místo konání akce

Almería

Datum konání akce

3. 6. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000502114100009