Integrated optimization of parallel robot performance for advanced manufacturing systems

这项研究计划将开发一种针对并联机器人的综合优化技术，以实现高精度、高适应性和低成本，走向更工业化的应用和新应用的变革性创新。 拟议研究计划的总体目标是开发一种新技术，其中包括：(I)提供支持并行机器人系统日益增长的应用的知识和专业知识；(Ii)将先进机器人的当前知识状态扩展到高性能机器人机器，以增强现有生产系统；(Iii)通过高性能可重构并联机器人促进可持续制造系统的发展。 具体地说，本研究确定了四个研究目标：(I)研究多目标优化方法对并联机器人系统性能(精度)的改善；(Ii)开发一种新的包括新的热效应误差模型的并联机器人系统的最优标定方法；(Iii)研究一种新的控制范式，称为通过设计控制，以全面提高性能；(Iv)开发一种新的适应性更好的方法(通过健壮设计和机器人重构)。 拟议的研究计划将开发的技术基于两个新的范式：集成优化(IO)和通过设计控制(CTD)。研究的意义在于开发新技术，为制造应用中的下一代机器人系统带来更好的设计方法，以及产生如何设计和更好管理制造机器人系统的新技术的更大潜力，使其性能达到新的最优。

This research program will develop an integrated optimization technology for parallel robots to achieve high accuracy, high adaptability and low cost towards a more industrial application and transformative innovation for new applications. The overall goal of the proposed research program is to develop a new technology which includes: (i) provide the knowledge and expertise in support of growing applications of parallel robotic systems; (ii) extend the current state of knowledge in advanced robotics to high performance robotic machines to enhance the existing production systems; (iii) facilitate the development of sustainable manufacturing systems by high performance reconfigurable parallel robotics. Specifically, four research objectives are defined for this research: (i) study the performance (accuracy) improvement for parallel robotic systems with multi-objective optimization methods; (ii) develop a novel optimal calibration method for parallel robotic systems including a new thermal effect error model; (iii) study a new control paradigm, called "control through design" for overall performance enhancement; and (iv) develop a new method for better adaptability (through robust design and robot reconfiguration). The technology to be developed by the proposed research program is based on two new paradigms: Integrated Optimization (IO) and Control through Design (CTD). The significance of the research lies in the development of new technologies that will lead to better design methodologies for next-generation robotic systems in manufacturing applications, as well as a higher potential to generate new technology of how to design and better manage manufacturing robotic systems, so that their performance can reach the new optimum.