Heterogeneous multi-robot system for mapping environmental variables of greenhouses

The productivity of greenhouses highly depends on the environmental conditions of crops, such as temperature and humidity. The control and monitoring might need large sensor networks, and as a consequence, mobile sensory systems might be a more suitable solution. This paper describes the application of a heterogeneous robot team to monitor environmental variables of greenhouses. The multi-robot system includes both ground and aerial vehicles, looking to provide flexibility and improve performance. The multi-robot sensory system measures the temperature, humidity, luminosity and carbon dioxide concentration in the ground and at different heights. Nevertheless, these measurements can be complemented with other ones (e.g., the concentration of various gases or images of crops) without a considerable effort. Additionally, this work addresses some relevant challenges of multi-robot sensory systems, such as the mission planning and task allocation, the guidance, navigation and control of robots in greenhouses and the coordination among ground and aerial vehicles. This work has an eminently practical approach, and therefore, the system has been extensively tested both in simulations and field experiments.The research leading to these results has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+ D en la Comunidad de Madrid and co-funded by Structural Funds of the EU, and from the DPI2014-56985-Rproject (Protección robotizada de infraestructuras críticas) funded by the Ministerio de Economía y Competitividad of Gobierno de España. This work is framed on the SAVIER (Situational Awareness Virtual EnviRonment) Project, which is both supported and funded by Airbus Defence & Space. The experiments were performed in an educational greenhouse of the E.T.S.I.Agrónomos of Technical University of Madrid.Peer Reviewe

Bayesian networks applied to climate conditions inside a naturally ventilated greenhouse

The prediction of gradients in a naturally ventilated greenhouse is difficult to achieve, due to the inherently stochastic nature of the airflow. Bayesian networks are numerical uncertainty techniques that can be used to study this problem. A set of experimental data was obtained: air temperature, air humidity, wind speed, and CO2 concentration at one and three meters above the ground in the growing space. The data set was discretized and used to develop a Bayesian Network model that describes the relationships between the studied variables. The model shows the differences that allow to identify the degree of dependence of the variables, as well as to quantify their inference

DISEÑO DE SISTEMA DE CONTROL EN UN INVERNADERO BASADO EN ROBÓTICA EDUCATIVA NEURON

Para el cultivo de verduras y hortalizas en un invernadero es importante monitorear y controlar variables como la humedad del suelo, la luminosidad y la temperatura ambiente. Este proyecto tiene como objetivo diseñar un sistema de control de invernadero inteligente, utilizando el kit de robótica educativa Neuron. Mediante la implementación de programación por bloques es posible desarrollar algoritmos de fácil entendimiento que permitan monitorear y controlar estas variables para aumentar la productividad de la cosecha de verduras y hortalizas en el municipio de Santa María. Con el desarrollo del proyecto se logró determinar que el kit Neuron es aplicable al desarrollo de soluciones de la cuarta revolución industrial en diferentes escenarios bajo el enfoque STEAM, entre ellos el monitoreo de variables de un invernadero, así mismo, se validó la pertinencia del proyecto en el municipio y se diseñó un sistema de monitoreo y control de la humedad del suelo, luminosidad y temperatura ambiente para ser aplicado a un invernadero inteligent

Proyecto PRIC: Protección Robotizada de Infraestructuras Críticas

Esta comunicación resume los trabajos realizados por el Grupo de Robótica y Cibernética (RobCib) del Centro de Automática y Robótica (CAR), formado por UPM y CSIC, en el contexto del proyecto PRIC (Protección Robotizada de Infraestructuras Críticas). Este proyecto tiene como objetivo el desarrollo de sistemas robóticos capaces de vigilar las infraestructuras críticas, detectando las potenciales amenazas e interviniendo cuando sea necesario. Algunos de estos trabajos están encaminados a la detección de anomalías visuales y acústicas, la detección, predicción e interceptación de intrusos, el desarrollo de un robot de pequeño tamaño y un manipulador híper-redundante para intervenir en áreas de difícil acceso, el diseño de una interfaz para misiones multi-robot y la adaptación de herramientas comunes en el mundo de la robótica a los escenarios multi-robot

Semi-autonomous drone for agriculture on the tractor base

This paper deals with the prospects of using a drone for spraying the gardens and vineyards. Relevance of this process is substantiated with the help of statistical data on the industry in Ukraine. To increase the efficiency of drones during the plant treatment, the concept of a semi-autonomous drone is proposed with connection to a communication line with a tractor – a “tractor-drone” complex. A spraying solution and commands for the drone are transmitted via the communication line. Basic physical formulas for appropriate selection of technical means for the lifting of sprayer frame are presented. Environmental parameters for the flight control system were estimated: temperature fluctuation at 20 K requires screw speed increase by 1.5%; an increase in atmospheric pressure by 5% allows reduction of screw speed by 2%. Tasks of the control system for the concept of semi-autonomous drones are defined in the paper

Sistema Móvil de Monitoreo de Gases en el Ambiente (SIMA)

El siguiente artículo busca dar a conocer el proyecto sobre el desarrollo de un sistema móvil de monitoreo de gases y condiciones medioambientales tipo nodriza. En el cual se usan robots controlados remotamente, estos robots están instrumentados con un sistema de adquisición y transmisión de datos de forma inalámbrica en tiempo real. Estos datos son recibidos por un software que organiza y permite visualizar los datos al operario por medio de una interfaz gráfica. La primera etapa que se abordo fue el rediseño del sistema mecánico que debía tener características de movilidad imprescindibles ya que inicialmente, se contaba un prototipo   que no cumplía con dichos parámetros o características. La segunda etapa fue establecer el enfoque eléctrico y electrónico, que permitiera la obtención de estos datos. La herramienta clave para la implementación de este proyecto fue los sensores MQ, que tienen la capacidad de medir el nivel diferentes gases

Robots in Agriculture: State of Art and Practical Experiences

The presence of robots in agriculture has grown significantly in recent years, overcoming some of the challenges and complications of this field. This chapter aims to collect a complete and recent state of the art about the application of robots in agriculture. The work addresses this topic from two perspectives. On the one hand, it involves the disciplines that lead the automation of agriculture, such as precision agriculture and greenhouse farming, and collects the proposals for automatizing tasks like planting and harvesting, environmental monitoring and crop inspection and treatment. On the other hand, it compiles and analyses the robots that are proposed to accomplish these tasks: e.g. manipulators, ground vehicles and aerial robots. Additionally, the chapter reports with more detail some practical experiences about the application of robot teams to crop inspection and treatment in outdoor agriculture, as well as to environmental monitoring in greenhouse farming

Simultaneous deployment and tracking multi-robot strategies with connectivity maintenance

Multi-robot teams composed of ground and aerial vehicles have gained attention during the last few years. We present a scenario where both types of robots must monitor the same area from different view points. In this paper, we propose two Lloyd-based tracking strategies to allow the ground robots (agents) to follow the aerial ones (targets), keeping the connectivity between the agents. The first strategy establishes density functions on the environment so that the targets acquire more importance than other zones, while the second one iteratively modifies the virtual limits of the working area depending on the positions of the targets. We consider the connectivity maintenance due to the fact that coverage tasks tend to spread the agents as much as possible, which is addressed by restricting their motions so that they keep the links of a minimum spanning tree of the communication graph. We provide a thorough parametric study of the performance of the proposed strategies under several simulated scenarios. In addition, the methods are implemented and tested using realistic robotic simulation environments and real experiments