AIARA: Artificial Intelligence Enabled Highly Adaptive Robots for Aerospace Industry
AIARA: Artificial Intelligence Enabled Highly Adaptive Robots for Aerospace Industry
批准号:
543881-2019
负责人:
Najjaran, Homayoun
金额:
$9.62万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31
中文摘要
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英文摘要
Agile manufacturing by the use of adaptive robots is the provision of advanced manufacturing, Industry 4.0, to enable more efficient, lean and cost-effective production of customized, large-scale but small batch size products. It is considered to be the ultimate solution for manufacturing industries hindered by their heavy reliance on manual labor. Aerospace industry is one of those industries that suffers greatly from lack of automation causing a backlog of new aircraft orders and prevents it from moving fast enough to adopt more efficient aircraft designs and advanced materials. An increased level of automation via the use of robots in manufacturing new aircrafts is pressing for not only cost reduction but also improved quality and safety in the aerospace industry. However, traditional industrial robots used in assembly lines of automotive industry and electronic devices is inadequate for the aerospace industry, because of small batch sizes, large components, diversity of products and a high level of complexity and variation in operations. Thus, the current practice of programming or teaching a robot for every specific task is limited, if not futile, in the aerospace industry. In advanced manufacturing and Industry 4.0, robots are intelligent, highly adaptive and can be trained to handle different equipment, tools, products and materials without a need for explicit programming. However, artificial intelligence-based learning methods require a large volume of data for capturing all possible physical experiences to train the robot, which can be too expensive or unavailable. Recent advances in robotics demonstrate the feasibility of learning from synthetic robot experiences and simulations. In the proposed project, we aim to develop a methodology to use learning results from simulation and virtual environments to robustly train a multi-arm adaptive robot for a wide range of aerospace manufacturing processes. This research partnership brings together the UBC, Kinova Inc., and Element AI, both prominent Canadian companies in the hi-tech sector, and in collaboration with the German Aerospace Centre DLR to build solutions for more effective manufacturing in aerospace industry.
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