Learning-based autonomous robotic system for package sorting application

用于包裹分拣应用的基于学习的自主机器人系统

• 批准号: 575195-2022
• 负责人: Alirezaee, ShahpourSDR
• 金额: $ 3.64万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760464
• 关键词: Learning; based; autonomous; robotic; system

With the advent of e-commerce and logistics industry, numerous goods are delivered every day. The COVID-19 pandemic-driven lockdown has forced businesses and customers to use e-commerce systems in order to sell or purchase products and services online. Sorting systems play a pivotal role in orders delivery practices. Typically, sorting systems consist of a mix of conveyors tied together which are controlled by the Warehouse Management System (WMS). Traditional objects sorting lines rely on human operators to locate and pick each product by hand. Such systems are labour-intensive, time-consuming, and error-prone, resulting in multiple counts to be done on a regular basis. To remedy these problems, automated sorting systems have been adopted. Despite the previous efforts, most robotic sorting systems fail to work in a complex environment for real-life applications. In these situations, robots should be able to recognize objects with various physical characteristics accurately and sort them quickly. To this end, an autonomous sorting robot should have the following capabilities: (i) detection and classification of objects with different shapes, sizes and physical properties, (ii) optimal object grasping, and (iii) trajectory generation and motion planning within the 3D environment. To fulfill these requirements, we will combine state-of-the-art computer vision algorithms with artificial intelligence methods to develop an autonomous robotic system for sorting packages in a real-world environment. This project will considerably benefit Canada in the following ways. (i) A wide range of Canada's industries will benefit from the proposed automated sorting system. The outcomes of this project have positive impacts on production, warehousing, inventory planning, and transportation sectors. (ii) The need for state-of-the-art technologies in this project will increase job opportunities for High Quality Personnel (HQP) in Canada and train them for real-world engineering applications. (iii) This project will precipitate the growth of Canada's e-commerce and logistic industry to increase its market share in the global market.

随着电子商务和物流业的出现，每天都有大量的货物被运送出去。新冠肺炎疫情导致的封锁迫使企业和客户使用电子商务系统在网上销售或购买产品和服务。分拣系统在订单交付实践中发挥着关键作用。通常情况下，分拣系统由捆绑在一起的输送机组成，这些输送机由仓库管理系统（WMS）控制。传统的物品分拣线依靠人工操作员手动定位和挑选每件产品。这类系统劳力密集、耗时且容易出错，导致需要定期进行多次计数。为了解决这些问题，采用了自动分拣系统。尽管之前的努力，大多数机器人分拣系统无法在复杂的环境中工作，无法在现实生活中应用。在这些情况下，机器人应该能够准确地识别具有各种物理特征的物体，并快速地对它们进行分类。为此，自主分拣机器人应具备以下能力：(1)对不同形状、大小和物理性质的物体进行检测和分类；(2)对物体进行最佳抓取；(3)在三维环境中进行轨迹生成和运动规划。为了满足这些需求，我们将结合最先进的计算机视觉算法和人工智能方法，开发一个在现实环境中分拣包裹的自主机器人系统。这个项目将在以下方面给加拿大带来很大的好处。(i)加拿大的许多工业将受益于拟议的自动分拣系统。该项目的成果对生产、仓储、库存规划和运输部门产生积极影响。（ii）本项目对最先进技术的需求将增加加拿大高素质人才的就业机会，并对他们进行实际工程应用方面的培训。（三）该项目将促进加拿大电子商务和物流业的发展，提高加拿大在全球市场的占有率。