For an intelligent agricultural robot to reliably operate on a large-scale farm, it is crucial to accurately estimate its pose. In large outdoor environments, 3D LiDAR is a preferred sensor. Urban and agricultural scenarios are characteristically different, where the latter contains many poorly defined objects such as grass and trees with leaves that will generate noisy sensor signals. While state-of-the-art methods of state estimation using LiDAR, such as LiDAR odometry and mapping (LOAM), work well in urban scenarios, they will fail in the agricultural domain.
3D Move To See (3DMTS) is a mutli-perspective visual servoing method for unstructured and occluded environments, like that encountered in robotic crop harvesting. This paper presents a deep learning method, Deep-3DMTS for creating a single-perspective approach for 3DMTS through the use of a Convolutional Neural Network (CNN). The novel method is developed and validated via simulation against the standard 3DMTS approach.
This paper proposes a bionic electric spraying rod to perform the crop watering and spraying in the farm. The design concept of multiple vertebrae structures of snake is used to realize a reproducible snake bone arm and muscles of snake, which can be regarded as multiple sets of thin wires and be pulled and released through driver module. It results in different attitudes of the snake bone arm. A water pipe is installed in the snake arm connected to the spray nozzle for spraying. The mobile application interface (APP) is designed to provide the user to control the arm remotely.
In this paper is proposed to conduct a first stage AKIS diagnostic exercise developing a map of the system of the actors involved in water quality protection and catchment management that interact with the farming community. Specifically we will use the tool to understand: (a) Who are the players? (b) What roles do they have? (c) what is their position in the Innovation System. A key part in changing the regulatory or public incentive system is to change the behaviour not only of the farmers but also of the policy makers to facilitate the movement to a more localised approach.
This paper has been prepared from a transcript of a presentation at the Crawford Fund 2017. This talk is a synthesis of some of the emerging issues we are seeing in the digital revolution, and how we can overcome the barriers to digitalised agricultural systems in the developing world
This paper relates the European Innovation Partnerships (EIP) to be implemented by Operational Groups (OGs) in Basilicata. New relationships and regeneration produced a “bio-economic Cluster”, creating “smart” specialization and a system linking research, innovation and the enterprise world. The Cluster consolidated competence and knowledge in small and medium enterprises, including agriculture and forest farms and encouraged the dissemination and implementation of innovative products and processes.
In the AgriSpin project (2015-2017) fifteen organisations involved in innovation support tried to understand better how each of them made a difference in helping farmers to innovate. In principle, each partner organisation hosted a Cross Visits of 3 – 4 days, to present a number of interesting innovation cases in which it was involved. The visiting team, composed of colleagues from other partner organisations, interviewed key actors in each case, and gave feedback about pearls, puzzlings and proposals in these innovation processes.
This research is dedicated to illuminating the relationship between knowledge and innovation within agrifood supply chains (ASCs) – although insightful and informative – is marked by conceptual and methodological issues that restrict our ability to understand the ways knowledge affects innovation and vice versa. In this work, adopting a systems approach to ASCs and synthesizing literature from different fields of study, we discuss the metaphors that guide research in this area, and we propose an alternative conceptualization of ASCs
This paper describes a novel approach to create a collaborative space for grassland innovations contributing to profitability of European grassland farms while preserving environmental benefits. Innovative modes of collaboration between practice and science are enabled by an international thematic network across eight European member states.
Based on three rounds of panel data (2007, 2009, and 2012) on indigenous households, this study assessed the impacts of Integrated Aquaculture-agriculture value chain participation on the welfare of marginalized poor indigenous rural households in Bangladesh. We also examined the distributional impacts of IAA value chain