50 research outputs found
Research in progress: Assessing marine radiocarbon reservoir effect variation in greater Utqiaġvik, Alaska
No abstract available
La (mancata) tutela dei diritti fondamentali frav sfide del costituzionalismo (inter)nazionale e disordine delle fonti del diritto
This paper aims at providing an overview of the nearly seventy years of challenges which have been coming along with (inter)national constitutionalism since its beginnings. Most of all, it aims at drawing attention to their peculiar relevance with regard to both the ever growing disorder of (national and international) legal sources and the wide and larger uncertainty in the forms to protecting fundamental rights and preserving fundamental goods (§ 5). In particular, after a few remarks on its (failed) achievements (§ 2), two sorts of challenges of the (inter)national constitutionalism will be distinguished: (i) the (earlier) challenges which even before the conclusion of the second world war had marked its beginnings and the slowly progressive assessment of its ultimate principles (§ 3); and (ii) the (new) challenges which at the conclusion of the cold war, in the contest of a new geopolitical disorder, have started to undermining its hardly achieved results as well as the basic values of its legal and political project (§ 4)
Acquiring plant features with optical sensing devices in an organic strip-cropping system
There is an increasing market for organic agriculture (Golijan & Popovi\vs, 2016). However, the lack of attention for biodiversity and soil fertility of current practices is a pressing issue. The SUREVEG project (CORE Organic Cofund, 2018) therefore looks at strip-cropping in organic production and its implementation in intensive farming to improve soil fertility and biodiversity throughout Europe. The aim is to enhance resilience (Wojtkowski, 2008), system sustainability, local nutrient recycling, and soil carbon storage (Wang, Li & Alva, 2010) among others. To counteract the additional labour of a multi-crop system, a robotic tool is proposed, which will operate upside down suspended from a wide-span mobile carriage. Within the project framework, a modular proof-of-concept (POC) version will be produced, combining sensing technologies with actuation in the form of a robotic arm. This POC will focus on fertilization needs, which are to be identified in real-time at the single-plant scale
Detección de características de cultivo a través de sensores ópticos en un sistema orgánico de tipo strip-cropping
Hay un mercado creciente para la agricultura orgánica. Sin embargo, la falta de atención a la biodiversidad y la fertilidad del suelo de las prácticas actuales es un tema urgente. En este contexto, el proyecto SUREVEG analiza el cultivo en franjas en la producción orgánica y su implementación en cultivos intensivos para mejorar la fertilidad del suelo y la biodiversidad en toda Europa. Para contrarrestar la mano de obra adicional de un sistema de cultivos múltiples, se propone una herramienta robótica. Dentro del marco del proyecto, se producirá una versión modular de prueba de concepto (POC) que combinará tecnologías de detección con la actuación en forma de un brazo robótico. Este sistema POC se centrará en las necesidades de fertilización, que se identificarán en tiempo real y se aplicarán en una sola planta. Este artículo se centra en la captación de las características del cultivo mediante nubes de puntos obtenidas con dos lidares y en su procesamiento
Definition of specifications for robotic prototype for strip-cropping systems
The SUREVEG project proposes the development and application of new organic cropping systems using strip-cropping and fertility strategies to improve resilience, system sustainability, local nutrient recycling and soil carbon storage. This document, entitled D4.1 Definition of specifications for robotic prototype, corresponds to
the first deliverable of WP4 in the SUREVEG project. It describes the technical specifications for the prototype, in order to automate the management of strip-cropping systems
Acquiring plant features with optical sensing devices in an organic strip-cropping system
The SUREVEG project focuses on improvement of biodiversity and soil fertility in organic agriculture through strip-cropping systems. To counter the additional workforce a robotic tool is proposed. Within the project, a modular proof of concept (POC) version will be produced that will combine detection technologies with actuation on a single-plant level in the form of a robotic arm. This article focuses on the detection of crop characteristics through point clouds obtained with two lidars. Segregation in soil and plants was successfully achieved without the use of additional data from other sensor types, by calculating weighted sums, resulting in a dynamically obtained threshold criterion. This method was able to extract the vegetation from the point cloud in strips with varying vegetation coverage and sizes. The resulting vegetation clouds were compared to drone imagery, to prove they perfectly matched all green areas in said image. By dividing the remaining clouds of overlapping plants by means of the nominal planting distance, the number of plants, their volumes, and thereby the expected yields per row could be determined.</p
Robotización del cultivo en hileras para la agricultura ecológica. Proyecto SUREVEG
La demanda de productos de agricultura ecológica está en auge, experimentando un continuo crecimiento. Este aumento de la demanda precisa de un crecimiento de la producción, que debe llevarse acabo sin renunciar al bajo impacto ambiental asociado a este tipo de agricultura. En este proyecto se trabaja en una herramiental robótica para automatizar la fertilización orgánica de cultivos en franjas
Detección de características de cultivo a través de sensores ópticos en un sistema orgánico de tipo strip-cropping
La demanda de los productos orgánicos está creciendo, por lo cual los agricultores tradicionales están viendo la necesidad de cambiar sus empresas. Sin embargo, la falta de atención a la biodiversidad y la fertilidad del suelo en la práctica actual pueden dañar la credibilidad de los productos orgánicos en general. Por eso el proyecto SUREVEG se enfoca en la producción orgánica en sistemas de tipo strip-cropping (cultivos mixtos en franjas) y en la aplicabilidad en la agricultura intensiva como manera para mejorar la fertilidad y biodiversidad en toda Europa. El objetivo es mejorar la resiliencia, la sostenibilidad del sistema, el reciclaje local de nutrientes y el almacenamiento de carbono en el suelo. Para contrarrestar la mano de obra adicional inherente a un sistema de cultivos múltiples, uno de los objetivos principales de este proyecto es el desarrollo de maquinaria automatizada para la gestión de los sistemas strip-cropping. Se propone una herramienta robótica suspendida de un carro de amplitud larga, similar a los sistemas de pórtico utilizados en la agricultura de tráfico controlado. Dentro del marco del proyecto, se producirá una versión modular de prueba de concepto, que combinará tecnologías de detección con la actuación en forma de un brazo robótico. Esta prueba de concepto se centrará en las necesidades de fertilización, que se identificarán en tiempo real y se aplicarán a nivel de plantas individuales.Los primeros enfoques de detección consisten en medidas con sensores lidar sobre varios campos de strip-cropping, para poder comparar la arquitectura de cultivos en bandas con su contraparte en monocultivos. La hipótesis es que el rendimiento del cultivo en bandas excede el rendimiento de los cultivos de la configuración tipo monocultivo, con una diferencia adicional esperada entre 'filas centrales' y 'filas de borde'. Esa diferencia se originaría debido a la interacción de especies vegetales mutuamente beneficiosas en los bordes del sistema de cultivos múltiples, lo cual produce un cambio significativo en la estructura de la planta y el volumen del dosel. En este trabajo se ha estudiado repollo en específico, con un enfoque en el volumen de la planta por área y su consistencia en todo el campo en dos configuraciones diferentes (monocultivo, frente a franjas). Con nubes de puntos obtenidos con lidares hacia el final de la temporada de crecimiento, se ha realizado una estimación del volumen del cultivo, que puede correlacionarse con las diferencias de rendimiento. Los primeros resultados confirman la hipótesis y proporcionan información útil para el desarrollo de un futuro vehículo robotizado de fertilización automatizada
Robotic Fertilization in Strip Cropping using a CNN Vegetables Detection-Characterization Method
To meet the increased demand for organic vegetables and improve their product quality, the Sureveg CORE Organic Cofund ERA-Net project focuses on the benefits and best practices of growing different crops in alternate rows. A prototype of a robotic platform was developed to address the specific needs of this field type at an individual plant level rather than per strip or field section. This work describes a novel method to develop robotic fertilization tasks in crop rows, based on automatic vegetable Detection and Characterization (D.a.C) through an algorithm based on artificial vision and Convolutional Neural Networks (CNN). This network was trained with a data-set acquired from the project’s experimental fields at ETSIAAB-UPM. The data acquisition, processing, anc actuation are carried out in Robot Operating System (ROS). The CNN’s precision, recall, and IoU values as well as characterization errors were evaluated in field trials. Main results show a neural network with an accuracy of 90.5% and low error percentages (<3%) during the vegetable characterization. This method’s main contribution focuses on developing an alternative system for the vegetable D.A.C for individual plant treatments using CNN and low-cost RGB sensors
ROBOFERT: Human - Robot Advanced Interface for Robotic Fertilization Process
The interfaces for Human-Robot interaction in different fields such as precision agriculture (PA) have made it possible to improve production processes, applying specialized treatments that require a high degree of precision at the plant level. The current fertilization processes are generalized for vast cultivation areas without considering each plant’s specific needs, generating collateral effects on the environment. The Sureveg Core Organic COfound ERA-Net project seeks to evaluate the benefits of growing vegetables in rows through the support of robotic systems. A robotic platform equipped with sensory, actuation, and communication systems and a robotic arm have been implemented to develop this proof of concept. The proposed method focuses on the development of a human-machine interface (IHM) that allows the integration of information coming from different systems from the robotized platform on the field and suggest to an operator (in a remote station) take a fertilization action based on specific vegetative needs to improve vegetable production. The proposed interface was implemented using Robot Operating System (ROS) and allows: visualizing the states of the robot within the crop by using a highly realistic environment developed in Unity3D and shows specific information of the plants’ vegetative data fertilization needs and suggests the user take action. The tests to validate the method have been carried out in the fields of the ETSIAAB-UPM. According to the multi-spectral data taken after (2 weeks after being planted) and before (3 months after growth), main results have shown that NDVI indexes mean values in the row crop vegetables have normal levels around 0.4 concerning initial NDVI values, and its growth was homogeneous, validating the influence of ROBOFER