Robot Highways

我们对未来软水果农业的愿景包括由可再生能源驱动的电动机器人和自主系统车队，这些系统可以采摘、运输、包装水果，同时收集数据，以最大限度地提高产量，减少浪费和对环境的影响。此外，这些技术通过减少部门对低技能劳动力的依赖，同时提高现有劳动力的技能，巩固了行业的可持续性。这一愿景可以在2025年实现。然而，大规模展示基础技术是至关重要的。这确保了一个重要的KE平台，为英国和全球供应链的转型提供了动力。我们的项目综合并展示了多个Innovate UK、Saga Robotics、林肯大学、Berry Garden Growers、H2020、UKRI-BBSRC、EPSRC和英国研究中心资助的研究和创新项目的成果。这将是全球已知的最大的机器人和自主（RAS）技术示范，该技术融合了单一农业系统中的多种应用技术。这将推动资源（碳、农药、水、废物）和劳动力（水果采摘、处理和物流）的生产力，同时支撑英国最具活力的农业食品部门之一（软水果）向零碳未来的过渡。机器人将用于优化物理农场流程，特别是运输和采摘水果、包装水果、处理作物以减少关键病虫害（UVC消除白粉病/害虫）和优化喷雾使用。此外，他们将通过收集数据来监控作物和水果的生长来控制虚拟农场。数据将使用人工智能和机器学习技术进行分析，以预测水果供应并优化农场生产力。机器人系统在大型商业农业系统中的应用将获得新的见解，特别是车队控制、收费和物流操作、数据处理资源（边缘/云）的优化以及调度大量数据所需的电信基础设施。目标可交付成果:1 \。在所有农场物流操作中消除化石燃料。减少90%的杀菌剂使用（通过UVC）和内在碳成本。减少30%的包装劳动力，减少40%的农场劳动力（加上与人员流动等相关的内在碳成本）。提高15%的农业生产力（每平方米产量）和内在碳收益。通过准确的预测，减少20%的水果浪费。

Our vision for future soft fruit farming encompasses fleets of electric robotic and autonomous systems powered by renewable energy that pick, transport, pack fruit whilst gathering data to maximise yield, reduce waste and environmental impacts. Additionally, these technologies underpin industry sustainability by reducing sector reliance on low skilled labour, whilst upskilling the existing workforce. This vision can be delivered by 2025\. However, it's critical the underpinning technologies are demonstrated at scale. This secures a significant KE platform to empower transformation across UK and global supply chains.Our project synthesises and demonstrates the outputs of multiple Innovate UK, Saga Robotics, University of Lincoln, Berry Garden Growers, H2020, UKRI-BBSRC, EPSRC and Research England funded research and innovation projects. It will be the largest known global demonstration of robotic and autonomous (RAS) technologies that fuse multiple application technologies (8) across a single farming system. These will drive resource (carbon, pesticide, water, waste) and labour (fruit picking, handling and logistics) productivity whilst underpinning the transition of one of UK's most vibrant agri food sectors (soft fruit) towards a carbon zero future. Robots will be deployed to optimise physical farm processes, in particular to transport and pick fruit, pack fruit , treat crops to reduce critical pests and diseases (UVC to eliminate powdery mildew / insect pests) and optimise spray use. In addition, they will control the virtual farm by collecting data to monitor crop and fruit growth. Data will be analysed using AI and machine learning technologies, pre-developed at Lincoln, to forecast fruit supply and optimise farm productivity. New insights will be gained in the application of robotic systems across large commercial farming systems, in particular fleet control, charging and logistics operations, optimisation of data processing resources (edge / cloud) and the telecommunications infra- structure required to dispatch large volumes of data. Target deliverables:1\. Elimination of fossil fuel across all farm logistic operations.2\. 90% reduction in fungicide use (by UVC) and intrinsic carbon cost.3\. 30% reduction in packhouse labour,40% reduction in farm labour (plus intrinsic carbon costs associated with people movement etc).4\. 15% increase in farm productivity (yield per m2) and intrinsic carbon gain.5\. 20% reduction fruit waste, through accurate forecasting.