The increasing public concern about food security and the stricter rules applied worldwide concerning herbicide use in the agri-food chain, reduce consumer acceptance of chemical plant protection. Site-Specific Weed Management can be achieved by applying a treatment only on the weed patches. Crop plants and weeds identification is a necessary component for various aspects of precision farming in order to perform on the spot herbicide spraying or robotic weeding and precision mechanical weed control. During the last years, a lot of different methods have been proposed, yet more improvements need to be made on this problem, concerning speed, robustness, and accuracy of the algorithms and the recognition systems. Digital cameras and Artificial Neural Networks (ANNs) have been rapidly developed in the past few years, providing new methods and tools also in agriculture and weed management. In the current work, images gathered by an RGB camera of Zea mays, Helianthus annuus, Solanum tuberosum, Alopecurus myosuroides, Amaranthus retroflexus, Avena fatua, Chenopodium album, Lamium purpureum, Matricaria chamomila, Setaria spp., Solanum nigrum and Stellaria media were provided to train Convolutional Neural Networks (CNNs). Three different CNNs, namely VGG16, ResNet–50, and Xception, were adapted and trained on a pool of 93,000 images. The training images consisted of images with plant material with only one species per image. A Top-1 accuracy between 77% and 98% was obtained in plant detection and weed species discrimination, on the testing of the images.

This paper set out to explore the precision agriculture (PA)-training needs of students studying in agricultural universities in the Euro-Mediterranean region (Greece, Italy, Portugal and Spain). SPARKLE is a Knowledge Alliance Project, funded by the European Union (EU), and one of its main goals is to narrow the innovation divide between entrepreneurship and the effective application of sustainable PA. During the project, the research conducted in all countries in the Euro-Mediterranean region revealed differences in the PA-training needs of university students. Additionally, this paper set out to explore the socioeconomic characteristics of students that affect their interest and knowledge towards PA. Finally, this paper aimed to understand the scope, present status and strategies for improving PA training in agricultural universities in the Euro-Mediterranean region. The following descriptive statistics and two multivariate analysis techniques were used: Two-Step Cluster Analysis (TSCA) and Categorical Regression (CATREG). Results support the notion that the lack of “PA knowledge/interest” adds to the technological gap amongst university students, slow adoption of PA and lower levels of overall rural economic development. These findings will be used as the fundamental cognition for the development of a joint action plan and several other national plans in the selected regions.

This topic will talk about the application of fleet robotics in agriculture. It will discuss the need for communications and the different strategies that could be implemented. It will also take a close look at how multi-robot systems are managed and supervised, as well as explain different planning strategies. The differences of centralised vs decentralised decision making will be explained, and an explanation of a graphical user interface will also be discussed.

This topic will talk about the different ways in which robotics can interact with its environment. It will dive into different actions necessary such as seeding, weeding, picking, spraying. It will not discuss the mechanical aspects in high details, but will be more in depth about the use of sensors and the decision making and reasoning of the way of work. It will also discuss the choices that need to be considered while designing for specific applications. Then this topic will also briefly mention data and monitoring applications, where the focus is mainly on the software capabilities, and not the hardware.

Mobility: This topic will use the framework introduced in the introduction to explain what mobility means, and what design choices are made for field operation. It will briefly discuss different sensing techniques, and will go in more depth on how a robot may use sensory input to make appropriate decisions for basic navigation as well as object avoidance. Finally, it will discuss path planning and its difficulties.

Introduction: This topic is the first of 4 Robotics topics, and contains a short introduction on what robotics is, its definition, and how it can help agriculture (in SPA). It will also lay the framework for the following topics within the lesson.