Creating Physical Structure from Disarray

食品业是英国制造业的一个主要部门，每年产值超过700亿英镑。机器人和自动化的引入将使工作人员从繁琐和繁重的任务中解放出来，但工艺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的多样性和加工过程中典型的缺乏物理秩序。生食产品通常被随机放置在传送带上，或堆放在散装容器中。虽然确实存在一些食品加工的自动化，但大多数都需要产品的定向进料。这是一名特工的典型任务，一旦被设备加工，产品往往会被弹回无序的排列！这项基础性和探索性的研究是开发自动化技术，将物理上无序的产品转换为适应产品和工艺变化的结构化安排。这将大大改善可自动化的食品和其他困难过程的范围，消除人们执行枯燥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增值任务。该项目将根据复杂性、输入感知和抓取要求对工业物理结构过程进行调查和分类。对于每个类别，将定义无序和有序状态的数学描述，并创建平移矩阵以在无序和有序排列状态之间转换。将使用该过程的动态建模来改进技术。同时，将为每一类确定适当的感官和处理技术。最后，将建立一个概念验证系统，以对食品部门的一些范例任务的新方法进行实物验证。这项研究将使机电一体化和自动化设计领域的学术界以及所有行业的工业用户和设备制造商受益，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.