SLAM: Suction, Localisation And Manipulation

Recycleye已经开发出一种低成本、由人工智能驱动的系统，它复制了人类视觉的力量。它使用先进的机器学习算法，在材料和对象层面上提供对混合废流中单个物品的自动、基于图像的检测。它利用了一条尖端的合成数据生成管道，以及Recycleye自己的WasteNet--世界上最大的标签废物可视化数据库。在之前资助的一个研发项目中，Recycleye用一个机械臂增强了视觉系统，以提供机器人分类解决方案。现在，Recycleye将开发和测试一种新型的机器人抓取技术，该技术将极大地提高Recycleye目前商业产品的拾取精度(从而提高效率)，使Recycleye的技术能够应用于城市固体废物(MSW)以外的废物流，同时为更广泛的工业自动化行业提供重大的技术发展，目前自动化行业中使用的拾取对象的方法是在抓取时瞄准被检测对象的中心。如果物品是扁平的，这是最佳的，然而在许多工业应用中，物品被压碎和变形，导致次优或失败的物品拾取。通过将最新的计算机视觉算法和技术应用于抓取问题，Recycleye将开发第一种可实时部署的最佳抓取预测技术，以在复杂的快节奏工业应用中保持准确性。这项技术在提高Recycleye公司在废物行业的系统能力方面具有巨大的潜力，同时在掌握与一系列行业相关的技术方面向前迈进了一步。

Recycleye has already developed a low-cost, AI-powered system replicating the power of human vision. It uses advanced machine learning algorithms to provide automatic, image-based detection of individual items in co-mingled waste streams, at a material and object level. It leverages a cutting-edge synthetic data generation pipeline, and Recycleye's own WasteNet - the world's largest visual database of labelled waste items.In a previously funded R&D project, Recycleye augmented the vision system with a robotic arm to deliver a robotic sorting solution. Now, Recycleye will develop and test a novel robotic grasping technology, that will drastically improve picking accuracy (and therefore the efficiency) of Recycleye's current commercial offerings, enabling the application of Recycleye's technology to waste streams beyond Municipal Solid Waste (MSW), whilst providing significant technical development for the wider industrial automation industry,The method currently used in automation industry when picking objects, is to aim for the centre of the detected object when grasping. This is optimal if the item is flat, however in numerous industrial applications items are crushed and deformed leading to a sub-optimal or failed item pick. By applying the latest computer vision algorithms and techniques to the grasping problem, Recycleye will develop the first optimal grasp prediction technology that can be deployed real-time to maintain accuracy in complex fast-paced industrial applications. This technology has a huge potential for boosting Recycleye's system capabilities within the waste industry, while providing a step forward in grasping technology relevant to a range of industries.