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Nimble Artificial Intelligence Driven Robotic Solutions for Efficient and Self-Determined Handling and Assembly Operations

Nimble Artificial Intelligence Driven Robotic Solutions for Efficient and Self-Determined Handling and Assembly Operations
灵活的人工智能驱动的机器人解决方案,可实现高效、自主的搬运和装配操作
批准号:
10048288
负责人:
金额:
$32.91万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
翻译
在过去的几年里,生产已经从大规模生产转向定制。传统上专注于一种产品变体或一个产品系列的传统生产线在应对新需求方面确实显示出局限性。此外,前所未有的全球事件,如最近的大流行危机,更表明需要灵活的生产系统,能够迅速将生产切换到完全不同的生产(例如,汽车制造商必须生产呼吸器、口罩等)。作为回应,MASTERLY旨在开发灵活的机器人解决方案,包括模块化抓手与最先进的机器人技术相结合,如移动、高低载荷工业和协作机器人以及智能起重机,并通过人工智能驱动的先进控制和感知能力进行增强,使它们能够自主行动,处理各种尺寸、形状和材料不同的零件,同时为男女员工所接受。这些发展将围绕以下五大支柱展开:1)采用多学科方法结合技术的创新,高效和低消耗的存储,检索,输送和取放系统2)强大的处理设备和系统,集成人工智能驱动的先进控制3)机器人/机器控制和编程的用户友好界面4)可互操作的S/W和H/W接口5)用于整条生产线的工件处理的工业试点案例。在三个不同生产部门的用例中,效率和用户接受度,旨在展示生产线和跨部门的适用性和适应性:电梯制造,专注于电梯电气柜的组装(KLEEMANN),运动服装,专注于仓库物流和包装(迪卡侬)和航空生产,专注于飞机机翼大型复合面板的生产(AERNNOVA)。
英文摘要
Over the last years, production has been shifted from mass production to customization. The conventional production lines, traditionally focused on one product variant or one family of products do show their limitations to cope with the new needs. Moreover, unprecedented worldwide events, such as the recent pandemic crisis, indicated even more the need for flexible production systems that can rapidly switch production to a totally different one (e.g. automotive manufactures had to produce respirators, facemasks etc.). As a response, MASTERLY aims to develop flexible robotic solutions, constituting of modular grippers combined with state-of-the-art robotic technologies, such as mobile, high and low payload industrial and collaborative robots and smart cranes, enhanced with AI driven advanced control and perception capabilities that will allow them to act autonomously, handling a large variety of parts varying in size, shape and material, while being acceptable by both genders of workforce. The developments will focus around the following 5 pillars: 1) Innovative, efficient and low consumption systems for storage, retrieval, conveying and pick-and-place using a multi disciplinary approach combining technologies 2) Robust handling devices and systems, with integrated –AI driven- advanced control 3) User-friendly interfaces for robot/machine control and programming 4) Interoperable S/W and H/W interfaces 5) Industrial Pilot Cases for work piece handling in full production line The technologies will be tested for flexibility, efficiency & user acceptance in three use cases from different productions sectors, aiming to demonstrate production line and cross sector applicability and adaptability: Elevators manufacturing, focusing on the assembly of electrical cabinets of lifts (KLEEMANN), Sportswear, focusing on warehouse logistics and packaging (DECATHLON) and Aeronautics production, focusing on production of large composite panels of aircraft wings (AERNNOVA).
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