Robust Data-Driven Control for Safety-Critical Systems

针对安全关键系统的稳健数据驱动控制

• 批准号: DP230101014
• 负责人: Prof Ian Manchester
• 金额: $ 30.29万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-07-11 至 2026-07-10
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP230101014
• 关键词: Robust; Data; Driven; Control; Safety

This project aims to develop new approaches to controlling robotic and cyber-physical systems in safety-critical applications. This project expects to generate new knowledge in how to harness the power of machine learning for robot control, while guaranteeing safety and stability at all times. The outcomes of this project will be new algorithms and a deeper understanding of the interplay of data, learning, and models, as well as experimental validation on a surgical robot and a bipedal walking robot. This project will provide significant benefits by dramatically increasing the range of applications in which the power of machine learning can be safely applied to advance the capabilities and uptake of robotics.

该项目旨在开发新的方法来控制安全关键应用中的机器人和网络物理系统。该项目预计将产生关于如何利用机器学习的力量进行机器人控制的新知识，同时确保始终安全和稳定。该项目的成果将是新的算法和对数据，学习和模型相互作用的更深入理解，以及对手术机器人和双足步行机器人的实验验证。该项目将通过大幅增加应用范围来提供显着的好处，在这些应用中，机器学习的力量可以安全地应用于提高机器人技术的能力和应用。