An optimized field coverage planning approach for navigation of agricultural robots in fields involving obstacle areas

Technological advances combined with the demand of cost efficiency and environmental considerations has led farmers to review their practices towards the adoption of new managerial approaches, including enhanced automation. The application of field robots is one of the most promising advances among automation technologies. Since the primary goal of an agricultural vehicle is the complete coverage of the cropped area within a field, an essential prerequisite is the capability of the mobile unit to cover the whole field area autonomously. In this paper, the main objective is to develop an approach for coverage planning for agricultural operations involving the presence of obstacle areas within the field area. The developed approach involves a series of stages including the generation of field‐work tracks in the field polygon, the clustering of the tracks into blocks taking into account the in‐field obstacle areas, the headland paths generation for the field and each obstacle area, the implementation of a genetic algorithm to optimize the sequence that the field robot vehicle will follow to visit the blocks and an algorithmic generation of the task sequences derived from the farmer practices. This approach has proven that it is possible to capture the practices of farmers and embed these practices in an algorithmic description providing a complete field area coverage plan in a form prepared for execution by the navigation system of a field robot

A Method to Quantify the Detailed Risk of Serious Injury in Agricultural Production

Agricultural injuries are a valuable social sustainability indicator. However, current methods use sector-scale production data, so are unable to assess the impact of changes in individual farming practices. Here, we developed a method that adopts a life cycle approach to quantify the number of serious injuries during agricultural production processes and assess the potential impact of changes in agricultural practices. The method disaggregates agricultural production into operations and estimates the contribution each operation makes to the frequency of different types of injuries. The method was tested using data collected by survey during an expert workshop in which sixteen participants were asked to estimate the parameters related to typical dairy cattle and pig farms. Parameter estimates for specific operations varied considerably between participants, so normalized values were used to disaggregate sector-scale statistics to production operations. The results were in general agreement with the results from other studies. Participants found it challenging to quantify the potential effect of new technologies. Provided suitable empirical statistical data are available, the method can be used to quantify the risk of injury associated with individual products and provide an ex-ante assessment of future developments in farming practices

Scenarios for European agricultural policymaking in the era of digitalisation

peer-reviewedCONTEXTDigitalisation affects the agri-food sector and its governance. However, what digitalisation of the sector will imply for future agricultural policymaking remains unclear. OBJECTIVEThe objective of the study is to develop and evaluate explorative scenarios of digitalisation in the agri-food sector of Europe that are explicitly relevant to agricultural policy. The study aims to provide guidance for strategic development of agricultural policy to address the potentials, uncertainties and unknowns arising with digitalisation of the sector. METHODSWe combine a Delphi study and a participatory scenario workshop to develop and evaluate plausible explorative scenarios of digitalisation of Europe's agri-food sector. For all scenarios we identify gaps in achieving a range of important European agricultural policy goals, drawing on the Delphi study and desk-based analysis. Subsequently we deduce strategies to address these agricultural policy gaps. RESULTS AND CONCLUSIONSFour scenarios of digitalisation of the agri-food sector were developed for Europe in 2030. They comprise of 1) digitalisation of the sector following current directions at current rates as a baseline scenario, 2) strong digitalisation of a regulatory government, 3) use of autonomous farming technology and 4) digitalised food business. These explorative scenarios entail various gaps in achieving European agricultural policy goals. Our findings suggest that the baseline scenario needs strategies to ramp up technological and institutional infrastructure for digitalisation. The other scenarios need strategies to prevent risks, e.g., of technological failures or undesired social impacts. They also need strategies to cater for special cases and diversity, e.g., of ecosystems and farming practices. Across the scenarios, it seems useful to increase digital competencies of the stakeholders. SIGNIFICANCEThe study is the first that derives implications for policy strategies from explorative scenarios of future digitalisation of agricultural systems that target gaps in achieving agricultural policy goals. The combination of developing and analysing scenarios generated findings that are of significance to policymaking stakeholders and researchers alike, who all need to address the uncertainties arising with future digitalisation of the agri-food sector