This paper describes a remote monitoring system of the agricultural robot using Web application. We developed the system in order to make clear condition about robot combine and adequately manage agricultural task data. The system makes the combine data accumulated in database so that it can be seen from remote-situated PC.
The paper presents an efficient approach for the modelling of wire robots kinematic and dynamics considering the effects of structural elasticity. Using the simulation and animation system several potential applications in agriculture have been simulated and analysed. The paper discusses possible robot configurations, system dynamic constraints and limits, as well as reachable performance for typical large-span wire robot applications in agriculture.
The objective of this research was to explore the use of data information of a low-cost IMU to provide an attitude angle with acceptable accuracy for agricultural robot navigation. This work was an attempt to create attitude angle estimation system via sensor fusion method based on gyroscope and accelerometer in this low-cost IMU. The used algorithm processed and integrated the data from triple gyroscope and tri-axis accelerometer using a low-pass filter and Kalman filter. Under this algorithm, experiment data showed that the estimation precision was improved effectively.
There is a growing concern by governments, retailers and consumers about the safety and quality of food. Because products are resourced on a on a global scale it becomes important that the origin of the products as well as all the treatments during production can be traced and that the production methods can be verified as good agricultural practices (GAP). This also includes considerations for the environment and sustainability.
The field of precision agriculture increasingly utilize and develop robotics for various applications, many of which are dependent on high accuracy localization and attitude estimation. Special attention has been put towards full attitude estimation by low-cost sensors, in relation to the development of an autonomous field robot. Quaternions have been chosen due to its continuous nature, and with respect to applications in the pipeline with on other platforms.
The European Innovation Partnership for agricultural productivity and sustainability (EIP-AGRI), which can be perceived as a platform based on interaction among farmers, researchers, and advisors/extensionists, represents a useful tool for a better understanding of applied innovation processes.
Multi-actors networks are increasingly used by farmers to link between them and to be interactively connected with other partners, such as advisory organizations, local governments, universities, and non-farm organizations. Given the importance assigned to the agricultural innovation by EU resorting to the networking between the research chain actors and the farmers, a strong focus on enhancing the creation of learning and innovation networks is expected.
Although innovation is understood to encompass much more than R&D, science continues to be an essential ingredient. In particular translation, adaptation and ‘valorisation’ of research results, the responsiveness of research to users’ needs and improved access to results are all regarded as important in achieving a more sustainable European agriculture. These challenges can be addressed in a number of ways including increased collaboration, networking, transdisciplinary research and co-operation between researchers and practitioners.
The private sector’s presence in agricultural advisory services worldwide has been on the increase for over three decades. This trend has also been observed in the Mantaro Valley (Peru), in a context of dairy family farming. The objective of the communication is to analyse the modalities of advisory services privatization and assess the consequences of this privatization for the farmers and their livestock systems. Data were collected through input suppliers, different types of advisers and producers interviews.
This paper outlines key areas of intervention that are identified as the core of FAO's strategy on strengthening Agricultural Innovation Systems (AIS) across multiple areas of work (e.g. research and extension, agroecology, biotechnology, green jobs, resourcing etc.) for achieving sustainable rural development.