Flottes de robots pour un contrôle phytosanitaire non nuisible pour l'environnement

Autor: George Kaplanis, César Fernández-Quintanilla, Pablo Gonzalez-de-Santos, Michael Brandstoetter, Manuel Pérez-Ruiz, Francisca López-Granados, Jaime del Cerro, Constantino Valero, Gilles Rabatel, Benoit Debilde, Slobodanka Tomic, Stefania Pedrazzi, Marco Vieri, Andrea Peruzzi, Angela Ribeiro, Gonzalo Pajares
Přispěvatelé: CENTER FOR AUTOMATION AND ROBOTICS UPM CSIC MADRID ESP, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), INSTITUTE OF AGRICULTURAL SCIENCES CSIC MADRID ESP, Instituto de Agricultura Sostenible - Institute for Sustainable Agriculture (IAS CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), COGVIS SOFTWARE AND CONSULTING GMBH VIENNA AUT, FTW FORSCHUNGSZENTRUM TELEKOMMUNIKATION WIEN GMBH VIENNA AUT, CYBERBOTICS SARL LAUSANNE CHE, UNIVERSITA DI PISA ITA, UNIVERSIDAD COMPLUTENSE DE MADRID ESP, TROPICAL S.A. ATHENS GRC, University of Sevilla, TECHNICAL UNIVERSITY OF MADRID ESP, UNIVERSITA DEGLI STUDI DI FIRENZE FLORENCE ITA, Information – Technologies – Analyse Environnementale – Procédés Agricoles (UMR ITAP), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), CASE NEW HOLLAND INDUSTRIAL ZEDELGEM BEL, European Commission, Consejo Superior de Investigaciones Científicas (España)
Rok vydání: 2016
Předmět:
Engineering
Fleets of robots
Agrochemical
Robótica e Informática Industrial
Agricultural robots
Autonomous robots
Multi-robot systems
Pest control
Agricultural and Biological Sciences (all)
Context (language use)
02 engineering and technology
Ingeniería Industrial
Pest control
Agricultural robots
Autonomous robots
Fleets of robots
Multi-robot systems
0202 electrical engineering
electronic engineering
information engineering
AUTONOMOUS ROBOTS
Production (economics)
PEST CONTROL
2. Zero hunger
Telecomunicaciones
Agricultural and Biological Sciences(all)
business.industry
Agricultura
Environmental engineering
04 agricultural and veterinary sciences
Environmental economics
Weed control
Variety (cybernetics)
FLEETS OF ROBOTS
Agriculture
AGRICULTURAL ROBOTS
[SDE]Environmental Sciences
040103 agronomy & agriculture
Food processing
MULTI-ROBOT SYSTEMS
0401 agriculture
forestry
and fisheries
Electrónica
020201 artificial intelligence & image processing
General Agricultural and Biological Sciences
business
Zdroj: Precision Agriculture
Precision Agriculture, Springer Verlag, 2017, 18, pp.574-614. ⟨10.1007/s11119-016-9476-3⟩
Precision Agriculture, ISSN 1573-1618, 2016-10-20
Archivo Digital UPM
Universidad Politécnica de Madrid
Digital.CSIC. Repositorio Institucional del CSIC
instname
ISSN: 1573-1618
1385-2256
Popis: González-de-Santos, Pablo et al.
Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. Within this context, this research strived to design, develop, test and assess a new generation of automatic and robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced end-effectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops.
The research leading to these results received funding from the European Union’s Seventh Framework Programme [FP7/2007-2013] under Grant Agreement nº 245986. Support for publishing this article has been provided by CSIC.
Databáze: OpenAIRE
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