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

如果机器人必须在黑暗中捡起一个苹果，我们应该构建一个复杂的基于人工智能的视觉系统还是只是“打开”灯？同样的挑战是让机器人在“恶劣的非结构化农业”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“结构性、可扩展性”改变“农场种植农产品的方式”，将收获“工作流程”简化为明确定义的任务，在这些任务中可以部署机器人以高效率执行“重复性、费力”的工作。 SCARLETT 是一个及时的可行性项目，因为人口结构变化（人口老龄化）、移民模式、气候变化、农场中执行“重复性、费力”任务的劳动力严重短缺等相互关联的挑战日益推动农业创新和采用自主机器人收割技术的趋势。**从工业工作单元中汲取灵感**，SCARLETT 设想“工作交给机器人”，例如重新设计收割过程以及在这样的环境中嵌入机器人/人工智能重要的是，创新是双向改造农场，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，增加产量来养活人口，同时提高资源效率和环境意识。

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.