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ANR funded project

RObotique et capteurs au Service d'Ecophyto (ROSE) 2017
Projet WeedElec2017

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

WEEDELEC 2017

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

Partners

AGRIAL STE COOP AGRICOLE ET AGRO-ALIMENTAI

CIRAD Centre de coopération internationale en recherche agronomique pour le développement

INRIA Institut National de Recherche en Informatique et en Automatique

IRSTEA IRSTEA

UMR EMMAH UMR Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes

ANR grant: 499 942 euros
Beginning and duration: janvier 2018 - 48 mois

 

ANR Programme: RObotique et capteurs au Service d'Ecophyto (ROSE) 2017

Project ID: ANR-17-ROSE-0003

Project coordinator:
Monsieur Vincent de RUDNICKI (IRSTEA)

 

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The project coordinator is the author of this abstract and is therefore responsible for the content of the summary. The ANR disclaims all responsibility in connection with its content.