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

High-voltage electrical weeding with adventitious detection and discrimination

The WeedElec project offers an alternative to global chemical weeding, which combines an aerial adventitious detection capability with a terrestrial robotic weeding solution using high-voltage electric power

Removal of glyphosate by a high voltage electric process of weeding seedlings.

The systematic use of pesticides is called into question with an awareness of the impact they have on the environment and human health. Pesticides were detected on 93% of the 2,360 stream quality monitoring stations. Groundwater is also contaminated. The most quantified substances are herbicides or their derivatives (glyphosate, AMPA, atrazine dethyl...) The ECOPHYTO Plan aims to reduce the use of plant protection products by 50% by 2025, with a first target of 25% by 2020. To achieve this, different means must be developed and combined: (i) bio-aggressor resistant varieties (ii) bio-control (iii) evolution towards pesticide-efficient farming systems (iii) innovative agroequipment, sensors and decision support tools.<br />The WeedElec project is directly in line with the objectives of ECOPHYTO. It addresses the problem of precision weeding by the original method of electric weeding, without any pesticides. In this sense, it goes beyond the target of a 50% reduction in the use of plant protection products, with certain limits in terms of speed and volume of treatment compared to current uses. In order to meet this expectation, it is necessary to be able to detect and locate adventices within the culture and then to destroy them electrically, all in an automatic and robust manner vis-à-vis conditions outside the field (light variability, biological variability, environmental hostility). This requires improving our scientific knowledge of plant identification using digital vision and artificial intelligence, as well as developing innovative destruction tools capable of effectively substituting chemical herbicides.

The project combines two complementary but independent detection approaches: (i) - an aerial detection approach focusing on the spatial location of «live« or «destroyed« adventices (post weeding) also usable for optimizing solutions using alternative methods of destruction, - (ii) - a ground-based approach using a robot with self-usable reconnaissance and precision destruction capabilities. The identification of species is based on the expertise acquired by Irstea in the processing of hyper-spectral images in the field, and by INRIA and CIRAD in the framework of the project Pl@ntNet ‘Artificial intelligence and deep-learning’.
The modeling of characterization processes and their integration into decision support tools, as well as the design of global weeding strategies, will be other scientific issues for which the consortium’s expertise will be required.
The destruction of high-voltage electrical adventices was previously the subject of research at IRSTEA in 1997-2000. It is an original way of destroying roots and aerial parts as glyphosate could. The proposed device helps to control the weed control and improve the efficiency of the destruction adapting the signal to the electrical impedance signature of plants (INRA) subjected to high voltage.
AGRIAL brings its expertise and means of real field experimentation.

Early results have helped develop the first solutions for detecting and discriminating weeds between them and seedlings to be preserved.
The first results reinforce our approach around the use of artificial intelligence and deep-learning techniques with the ambition of coupling with the hyper-spectral approach. The first tests of high voltage destruction are positive, although not yet using power and signal modulation.
Research on the signing of the adventitious impedance has defined the range of power and frequency that improves upon destruction.

WeedElec aims to lift, in particular, the following major scientific locks:
· Detection/identification of adventitious by hyper-spectral and color imaging, and associated deep-learning and chemometry techniques.
· The coupling of aerial detection and robot onboard detection to decide on the elimination of adventices.
· The HT electrical discharge coupling and complex adventitious impedance to determine the best high voltage action characteristics required.
We'll be interested in putting in place an integrated strategy of weeding on a typical robot.

No publications produced in 2019.
Demonstrations during the dryrun and ECPA 2019 and ANRT days


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 coordination

Claude DOUSSAN (UMR Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes)

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

Help of the ANR 499,939 euros
Beginning and duration of the scientific project: December 2017 - 48 Months

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