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

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20205 - Automation and control systems

Project

—

Continuities

O - Projekt operacniho programu

Publication year

2019

Confidentiality

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

Article name in the collection

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

ISBN

978-3-030-19650-9

ISSN

0302-9743

e-ISSN

1611-3349

Number of pages

15

Pages from-to

82-96

Publisher name

Springer Switzerland

Place of publication

Cham

Event location

Almería

Event date

Jun 3, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000502114100009