16AGRITECHCAT5: GrassVision: Automated application of herbicides to broad-leaf weeds in grass crops

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The aim of the project is to develop a novel spray apparatus for precision application of herbicides to broad-leaf weeds ingrass crops. Such a system, using a spray boom covering a 10x.5m area of ground, could feasibly run at upwards of 1m/s,allowing precision spraying of weeds at between 1 and 2 hectares/hr.The consortium is comprised of three partners; (1) Centre for Machine Vision (CMV), a leading research centre in 3Dmachine vision, with past success in the agri-tech field, (2) Aralia Systems Ltd (AS), an international security company witha wide R&D portfolio in data-mining and complex feature analysis on videos, (3) Soil Essentials Ltd (SE), a leadingprecision agriculture company specialising in GPS machinery guidance, implement control, cloud based decision supportsystems and emerging grassland agronomy technologies.The primary focus will be to detect weeds in grass such as dock and ragwort using novel 3D machine vision techniques. Initially theproject will use off-the-shelf machinery to spray an area of roughly 50x50cm around each weed, activating the relevantnozzles on the boom with an estimated aimed decrease in herbicide use of around 75%.The project will then look todetermine the limits of precision by refining the boom itself, allowing nozzles to move linearly across the boom as on aninkjet printer, or in rotation using servo motors. Using this approach, we aim to provide potential reductions in herbicide usein excess of 90%.The role of the CMV team will be to realise novel 3D imaging hardware and software for detecting the weeds in the grasswhile moving on a tractor. We also aim to recognise the weed species. This data will be used to both direct the automatedweeding system in real-time (developed by SE) and to create a detailed weed data map (developed by AS) of the entirefield.