Creating Physical Structure from Disarray

食品工业是英国制造业的一个主要部门，每年价值超过700亿英镑。机器人技术和自动化的引入将使工作人员从繁琐而艰巨的任务中解脱出来，但过程和产品的性质阻碍了许多当前自动化技术的直接应用。两个关键方面是食品产品的变化和加工过程中典型的缺乏物理秩序。生食品通常随机放置在传送带上，或堆放在散装容器中。虽然在食品加工中确实存在一些自动化，但大多数都需要产品的定向进料。这是一项典型的操作任务，一旦被设备处理，产品往往被弹射回一个混乱的安排！这项基础和冒险的研究是开发自动化技术，将物理无序的产品转化为结构化的安排，以适应产品和过程的变化。这将大大提高食品和其他可以自动化的困难过程的范围，消除了人们执行无聊的机器喂料任务的需要，并使生产者能够将宝贵的人力资源用于更多的增值任务。该项目将调查和分类工业物理结构过程的复杂性，输入传感和掌握要求。对于每个类别，将定义无序和有序状态的数学描述，并创建在无序和有序排列状态之间转换的平移矩阵。过程的动态建模将用于改进技术。同时，将为每个类别确定适当的感觉和处理技术。最后，将构建一个概念验证系统，以在食品部门的一些示例任务上物理验证新方法。这项研究将有利于机电一体化和自动化设计领域的学术界，以及所有工业部门的工业用户和设备生产商，他们将获得新设备的潜力，并拓宽现有自动化的应用领域。

The food industry is a major sector in UK manufacturing worth over 70bn per annum. The introduction of robotics and automation would free staff from tedious and arduous tasks, yet the nature of the processes and products hinder direct application of many current automation techniques. Two key aspects are the variation in food products and the typical lack of physical order in their processing. Raw food products are commonly randomly positioned on conveyors, or heaped into bulk containers. Whilst some automation does exist for processing foods, the majority require oriented infeeding of products. This is a typical task for an operative, and once processed by the equipment the products are often ejected back into a disordered arrangement! This fundamental and adventurous research is to develop automation techniques for the translation of physically disordered products into structured arrangements accommodating variations in the products and processes. This will substantially improve the range of food and other difficult processes that can be automated, remove the need for people to perform boring machine feeding tasks, and enable the producers to use valuable human resource on more value-adding tasks.The project will survey and categorise industrial physical structuring processes in terms of complexity, input sensing, and grasping requirements. For each of the categories mathematical descriptions of the states of disarray and order will be defined and translational matrices created to transform between the disorder and ordered arrangement states. Dynamic modelling of the process will be used to improve the techniques. In parallel, appropriate sensory and handling technologies will be determined for each category. Finally a proof of concept system will be constructed to physically validate the new approaches on a number of example tasks from the food sector. This research will benefit the academic community in the fields of mechatronics and automation design, and industrial users and equipment producers from all industry sectors who will gain the potential for new equipment and broaden application areas for existing automation.