Detection and Localizing of Rumex Seedlings for Robotic Weeding

Niko Kansakoski, Tapio Heikkila, Jarkko Kotaniemi

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)

Abstract

Weeds are causing substantial losses for livestock farming and decrease land cultivability in farming. Treating weeds with herbicides is harmful for the environment and we are targeting automatic mechanical weeding of Rumex longifolius in pastures using mobile field robot technologies. We are relying on 2D/3D computer vision technologies and have developed an algorithmic solution for detecting seedlings of Rumex weeds. We show promising test results on weed detecting and lozalizing for robotic removal.
Original languageEnglish
Title of host publication18th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Proceedings (MESA 2022)
PublisherIEEE Institute of Electrical and Electronic Engineers
Number of pages7
ISBN (Electronic)978-1-6654-5570-1
ISBN (Print)978-1-6654-5571-8
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Article in a conference publication
Event18th International Conference on Mechatronic, Embedded Systems and Applications, IEEE/ASME MESA 2022 : Hybrid Event - National Taiwan University of Science and Technology International Building 202, Taipei, Taiwan, Province of China
Duration: 28 Nov 202230 Nov 2022

Conference

Conference18th International Conference on Mechatronic, Embedded Systems and Applications, IEEE/ASME MESA 2022
Country/TerritoryTaiwan, Province of China
CityTaipei
Period28/11/2230/11/22

Keywords

  • clustering
  • image local entropy
  • Machine vision
  • mobile robot
  • weed recognition

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