ROSE - RObotique et capteurs au Service d'Ecophyto

Site-specific weeding robot using high electrical voltage actuator combined with UAV hyperspectral imagery for predictive management and post-assessment. – WeedElec2017

Submission summary


We propose in this project an alternative solution to global chemical weeding, which combines aerial means for weed detection coupled with a robotized ground weeding system based on high voltage electrical energy.

The project will rely on commercial solutions concerning the aerial and ground vehicles (respectively UAV and robot). It will more particularly focus on major technical and scientific issues for the development of a future integrated weeding solution, i.e.:
- weed detection and identification, using hyperspectral imagery and deep learning techniques
- weed behavior when they are exposed to electrical stress, especially by investigating the relationship between the kind of electrical shock to be applied and the weed electrical impedance and phenology.

Questions related to aerial and robot-embedded weed detection systems will also be addressed, as well as possible environmental and safety effects of electrical shock usage on weeds, in order to design a safe integrated weeding strategy.

This project draws on previous results obtained in the FP4 European project Patchwork (electrical weeding 1995), in the FP7 European project RHEA (Integrated weeding solution, 2012) and on the Plant@Net project, devoted to automatic plant identification by deep learning. It also relies on the expertise of plant phenology scientists and weed scientists.

The WeedElec project will be an opportunity to enrich Plant@net image databases, to produce a database of electrical signatures of main weed species, to develop and test new robust algorithms for weed detection and identification, and to validate an innovative weeding solution with no chemicals.

The experimentations will be led in field crop and market gardening plots, in order to cover variate crop and weed typologies

Project coordinator

IRSTEA (Laboratoire public)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


UMR Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes
Centre de coopération internationale en recherche agronomique pour le développement
Institut National de Recherche en Informatique et en Automatique

Help of the ANR 499,942 euros
Beginning and duration of the scientific project: December 2017 - 48 Months

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