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＜departmental bulletin paper＞
Study on Improvement of Measurement Accuracy for External Sensor by Neural Network System

Creator
Author PID
K001580
Creator Name
井上, 英二
Inoue, Eiji
Affiliation
Affiliation Name
九州大学農学部農業機械学講座
Laboratory of Agricultural machinery, Faculty of Agriculture, Kyushu University
Creator Name
矢田, 恵子
Yada, Keiko
Affiliation
Affiliation Name
九州大学農学部農業機械学講座
Laboratory of Agricultural machinery, Faculty of Agriculture, Kyushu University
Author PID
K001522
Creator Name
橋口, 公一
Hashiguchi, Koichi
Affiliation
Affiliation Name
九州大学農学部農業機械学講座
Laboratory of Agricultural machinery, Faculty of Agriculture, Kyushu University
Creator Name
崔, 重燮
Choe, Jung-Seob
Affiliation
Affiliation Name
九州大学農学部農業機械学講座
Laboratory of Agricultural machinery, Faculty of Agriculture, Kyushu University
Creator Name
田代, 克己
Tashiro, Katsumi
Affiliation
Affiliation Name
九州大学農学部農業機械学講座
Laboratory of Agricultural machinery, Faculty of Agriculture, Kyushu University
Creator Name
山中, 捷一郎
Yamanaka, Shoichiro
Affiliation
Affiliation Name
九州大学農学部農業機械学講座
Laboratory of Agricultural machinery, Faculty of Agriculture, Kyushu University
Language
Japanese
Publisher
九州大學農學部
Faculty of Agriculture, Kyushu University
Date
2000-02
Source Title
Science bulletin of the Faculty of Agriculture, Kyushu University
Vol
54
Issue
3/4
First Page
141
Last Page
147
Publication Type
Version of Record
Access Rights
open access
JaLC DOI
https://doi.org/10.15017/23643
Related DOI
九州大學農學部學藝雜誌 || 54(3/4) || p141-147
Science bulletin of the Faculty of Agriculture, Kyushu University || 54(3/4) || p141-147
http://www.agr.kyushu-u.ac.jp/
Related URI
九州大學農學部學藝雜誌 || 54(3/4) || p141-147
Science bulletin of the Faculty of Agriculture, Kyushu University || 54(3/4) || p141-147
http://www.agr.kyushu-u.ac.jp/
Relation
九州大學農學部學藝雜誌 || 54(3/4) || p141-147
Science bulletin of the Faculty of Agriculture, Kyushu University || 54(3/4) || p141-147
http://www.agr.kyushu-u.ac.jp/

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Details

Record ID
23643
Peer-Reviewed
Unrefereed
ISSN
0368-6264
NCID
AN0005519X
Notes
The real time positioning system is necessary and essential for autonomous agricultural vehicles. In general, the external sensor used for positioning system equipped with vehicle has no practical use because of being unable to obtain the correct location information of a vehicle due to output error of a sensor. In this study, accuracy of the supersonic waves sensor which is used as the external sensor, was estimated, and further, the learning system of neural network (NN) was applied to decrease of output error of the sensor. As a result, error and fluctuation of sensor output became large according to revolutionary velocity of the sensor unit under the condition of measuring with sensor only. On the other hand, in case of revising a sensor output based on actual vehicles' location by the NN learning system, sensor output was almost in agreement with actual location without the influence of revolutionary velocity of the sensor unit. Consequently, the learning system of NN is available for improving the accuracy of external sensor as a positioning system of the autonomous vehicles.
圃場機械を自律走行させるためには,車両位置のリアルタイムの認識が必要不可欠となる.一般に位置認識に用いる外界センサはセンサの出力誤差により正確な位置情報が得られないため,現時点で使用するには実用的でない.そこで,本研究では外界センサの一つである超音波センサの出力誤差の確認を行い,ニューラルネットワーク(NN)の学習システムで出力誤差を軽減させることを試みた.その結果,センサのみでの位置情報ではセンサの回転速度の増加に伴い,誤差や変動が大きくなる傾向を示した.一方, NNにより実際の位置情報を学習させ,センサ出力の補正を行った結果,回転速度の影響によらず正確な安定した位置情報が得られることが検証された.以上より,自律走行車両に用いる外界センサの精度向上には, NNによる学習システムが有効であり,今後の実機への搭載・実用化に向けて寄与しうるものと考えられる.
Created Date 2012.07.31
Modified Date 2022.11.11

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