Autonomous Agricultural Robot – Testing of the Vision System for Plants/Weed Classification

Marcin Jasiński , Jędrzej Mączak , Przemysław Szulim , Stanisław Radkowski

Abstract

The aim of the paper was to present results of the vision system for plants/weeds classification testing of autonomous robot for sowing and wide row planting. Autonomous work of the robot in range of traction and agronomic processes will be implemented on the basis of data from a many sensors (cameras, position and distance). Positive test results will allow for the use of the robot in organic crops requiring mechanical removal of weeds or in crops with application of selective liquid agrochemicals limited to the minimum. Unless the control systems are improved and development costs are compensated, the production of autonomous agricultural systems will increase. So that very important is mentioned in this paper, vision system of plant/weed classification. The vision system for sugar beet/weed and sweet corn/weed classification was build and tested. The position of each plant must be determined for intra-row weeding. This means that plants have to be classified into two classes, i.e., sugar beet (sweet corn) or weed.
Author Marcin Jasiński (FACME / IAE)
Marcin Jasiński,,
- Institute of Automotive Engineering
, Jędrzej Mączak (FACME / IAE)
Jędrzej Mączak,,
- Institute of Automotive Engineering
, Przemysław Szulim (FACME / IAE)
Przemysław Szulim,,
- Institute of Automotive Engineering
, Stanisław Radkowski (FACME / IAE)
Stanisław Radkowski,,
- Institute of Automotive Engineering
Pages473-482
Publication size in sheets0.5
Book Szewczyk Roman, Zieliński Cezary, Kaliczyńska Małgorzata: Advances in Automation, Robotics and Measurement Techniques, Advances in Intelligent Systems and Computing, vol. 743, 2018, Springer International Publishing AG , ISBN 978-3-319-77178-6, 795 p., DOI:10.1007/978-3-319-77179-3
Keywords in EnglishAgriculture robot Care of plants Autonomous work Plant/weed classification Vision system
DOIDOI:10.1007/978-3-319-77179-3_44
URL https://link.springer.com/chapter/10.1007/978-3-319-77179-3_44
Languageen angielski
LicensePublisher website (books and chapters only); published final; Uznanie Autorstwa (CC-BY); after publication
Score (nominal)15
ScoreMinisterial score = 15.0, 24-03-2018, BookChapterSeriesAndMatConf
Ministerial score (2013-2016) = 15.0, 24-03-2018, BookChapterSeriesAndMatConf
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