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

如果一个机器人必须在黑暗中捡起一个苹果，我们是应该建立一个复杂的基于人工智能的视觉系统，还是只是打开灯？同样的挑战也是让机器人以人类的效率在恶劣的非结构化农业环境中工作，使其在商业上可行。Scarlett是一项雄心勃勃的项目，它将以“结构化、可伸缩性”的方式改变“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，在这些任务中，机器人可以高效率地执行“重复性、繁重的”工作。Scarlett是一个适时的可行性项目，因为不断变化的人口结构(人口老龄化)、移民模式、气候变化、农场劳动力严重短缺等相互关联的挑战正在日益推动农业创新和采用自主机器人收获技术的趋势。**从工业工作单元中获得灵感**，Scarlett设想了一个类似于收获过程的重新设计和Robotics/AI在这样一个环境中嵌入的“机器人的工作”。重要的是，创新是对农场的双向改造，整合机器人来高效地执行半结构化任务。斯嘉丽将缓解该行业面临的劳动力短缺，增加产量以养活人口，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.