SCARLETT - SCAlable, structured and Resource efficient indoor robotic harvesting of LETTuce

SCARLETT - 可扩展、结构化且资源高效的室内机器人收获生菜

• 批准号: 10028018
• 金额: $ 45.03万
• 依托单位: JEPCO (GLEBE) LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10028018
• 关键词: SCARLETT; SCAlable; structured; Resource; efficient

If a robot had to pick up an apple in darkness, should we build a complex AI based vision system or just 'switch on' the light? The same is the challenge of getting robots working in 'harsh unstructured agricultural' settings with humanlike efficiency to be commercially viable. SCARLETT is an ambitious project that instead transforms how 'produce is grown in the farm' with 'structure, scalability', simplifying the harvesting 'workflows' into well-defined tasks where robots can be deployed to perform 'repetitive, laborious' jobs with high efficiency. SCARLETT is a timely feasibility proejct becasue interlinked challenges like changing demographics (ageing population), immigration patterns, climate change, critical shortage of labour to perform 'repetitive, laborious' tasks in the farm are increasingly driving the trend towards farming innovation and adoption autonomous robotic harvesting technologies.**Taking inspiration from industrial work cells**, SCARLETT envisions a 'work goes to robots' like redesign of harvesting process and embedding of Robotics/AI in such an environment Importantly, the innovation is bidirectional- modification of the farm, integration of robots to perform semi-structured tasks with high efficiency. SCARLETT will mitigate labour shortage faced by the industry, increase production to feed the population while being resource efficient and environment aware.

如果一个机器人必须在黑暗中捡起一个苹果，我们应该建立一个复杂的基于人工智能的视觉系统，还是仅仅“打开”灯？同样的挑战是让机器人在“严酷的非结构化农业”环境中以类似人类的效率工作，以实现商业可行性。SCARLETT是一个雄心勃勃的项目，它通过“结构、可扩展性”改变了“农场中的农产品种植”方式，将收获“工作流程”简化为定义明确的任务，可以部署机器人以高效率执行“重复、费力”的工作。SCARLETT是一个及时的可行性项目，因为不断变化的人口结构（人口老龄化）、移民模式、气候变化、农场中执行“重复、繁重”任务的劳动力严重短缺等相互关联的挑战正在越来越多地推动农业创新和采用的趋势自动机器人收割技术。**从工业工作单元 ** 中获得灵感，SCARLETT设想了一种“工作到机器人”，如重新设计收割过程和在这样的环境中嵌入机器人/人工智能。重要的是，创新是双向的-修改农场，集成机器人以高效率执行半结构化任务。SCARLETT将缓解该行业面临的劳动力短缺问题，提高产量以养活人口，同时提高资源效率和环境意识。