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Structural Synthesis and Performance Study of Generalized Parallel Manipulators

Structural Synthesis and Performance Study of Generalized Parallel Manipulators
广义并联机构的结构综合与性能研究
批准号:
RGPIN-2022-04624
负责人:
Zhang, Dan
金额:
$4.01万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
背景:机器人技术通过节省成本、改善产品质量和工作条件,为制造业带来了革命性的变化。在制造业中继续有效地使用机器人技术对未来的经济增长、创造就业机会和全球竞争力至关重要。满足这些要求的一个总趋势是使用被称为传统并联机械手(CPM)的机器人。与串联机械手相比,CPM具有更高的刚性、精度和承载能力。尽管有这些优点,但CPM在运动链之间的耦合方面仍然面临挑战,因此由于其性能能力的限制而没有被工业广泛采用。研究计划:拟议的研究计划侧重于下一代并联机器人--通用并联机器人(GPM)--可以克服CPM的限制,更快、更准确地执行任务,具有更大的工作空间和对不断变化的工作任务和条件的更强适应能力。其长期目标是开发用于GPM结构合成的设计方法,开发用于提高GPM性能的理论,并通过关注关键的技术差距和严格的实验,使这些技术能够转移到工业应用中。短期目标是研究和开发:(1)具有可配置平台的GPMS,以实现更好的任务适应性;(2)具有耦合子链的GPMS,以获得更高的刚度;(3)具有铰接式移动平台的GPMS,以实现更大的工作空间;以及4)可重新配置的GPMS,以获得更好的性能。我们将使用两种新的范式:面向性能的设计(DFP)和系统集成(SI)来开发高性能GPM的新设计方法和技术。DFP范例生成了一个集成环境,使得能够同时设计机器人结构和开发最佳系统性能。SI方法协同集成各个组件,以最大限度地发挥它们的互补优势,最大限度地减少它们的弱点。意义:拟议的研究计划将对下一代全球定位系统的设计和方法及其在现代制造领域的实际应用做出重大贡献。开发的GMP将促进制造操作,包括更高精度的组装、更快的产品处理和表面处理,以及更智能的生物医学仪器(例如,可穿戴设备)。这项研究还将通过提高性能和效率,提高质量和灵活性,降低目前在加拿大工业中使用的许多机器人产品的成本和交货期,对加拿大制造业经济和先进制造业(包括汽车和航空航天)产生重大影响。此外,拟议的研究将培养下一代HQP,以满足工业对基础科学发现和工业应用创新的日益增长的需求。
英文摘要
BACKGROUND: Robotics has revolutionized the manufacturing industry by saving costs, and improving product quality and work conditions. Continued effective use of robotics in manufacturing is essential to future economic growth, job creation and global competitiveness. A general trend of meeting these demands is to make use robots called Conventional Parallel Manipulators (CPMs). As compared to serial manipulators, CPMs have higher rigidity, accuracy, and loading capacities. Despite these advantages, CPMs still suffer from challenges in coupling between kinematic chains and thus are not being widely adopted by industry due to limitations in their performance capabilities. RESEARCH PROGRAM: The proposed research program focuses on the next-generation of parallel manipulators -- Generalized Parallel Manipulators (GPMs) -- that can overcome the limitations of CPMs and perform tasks faster, more accurately, with larger workspace and greater adaptability to changing work assignments and conditions. The long-term objectives are to develop design methodologies for structural synthesis of GPMs, to develop theories for improving performance of GPMs, and to enable technology transfer of these techniques to industry applications by focusing on the critical technology gaps and rigorous experiments. The short-term objectives are to study and develop: (1) GPMs with configurable platforms for more task adaptability; (2) GPMs with coupling sub-chains for higher stiffness; (3) GPMs with articulated moving platforms for larger workspace; and 4) reconfigurable GPMs for better performance. We will use two new paradigms: Design For Performance (DFP) and System Integration (SI) to develop new design methodologies and technologies for high performance GPMs. The DFP paradigm generates an integrated environment that enables simultaneous design of a robot structure and development of an optimal system performance. The SI approach synergistically integrates components to maximize their complementary strengths and minimize their weaknesses. SIGNIFICANCE: The proposed research program will lead to substantial contributions to the design and methodologies of next-generation GPMs and their practical applications in modern manufacturing fields. The GMPs developed will facilitate manufacturing operations that include higher precision assembly, faster product handling and surface finishing, and smarter biomedical instruments (e.g., wearable device). This research will also significantly impact the Canadian manufacturing economy and advanced manufacturing sectors, including automotive and aerospace, by improving performance and efficiency, increasing quality and flexibility, and lowering costs and lead time of many robotic products currently used in Canadian industries. In addition, the proposed research will train the next-generation of HQP needed to meet the increasing needs of industry for both fundamental scientific discovery and innovations in industrial applications.
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会议论文
High Performance, Intelligent and Efficient Robotic Systems: Performance Integration, Decomposition and System Hybridization
  • 批准号:
    RGPIN-2016-05030
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.35万
  • 财政年份:
    2021
  • 负责人:
    Zhang, Dan
  • 依托单位:
High Performance, Intelligent and Efficient Robotic Systems: Performance Integration, Decomposition and System Hybridization
  • 批准号:
    RGPIN-2016-05030
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.35万
  • 财政年份:
    2020
  • 负责人:
    Zhang, Dan
  • 依托单位:
High Performance, Intelligent and Efficient Robotic Systems: Performance Integration, Decomposition and System Hybridization
  • 批准号:
    RGPIN-2016-05030
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.35万
  • 财政年份:
    2019
  • 负责人:
    Zhang, Dan
  • 依托单位:
The Role of Notch Signaling in Caenorhabditis elegans Germline Stem Cells
  • 批准号:
    542662-2019
  • 项目类别:
    Alexander Graham Bell Canada Graduate Scholarships - Master's
  • 资助金额:
    $1.27万
  • 财政年份:
    2019
  • 负责人:
    Zhang, Dan
  • 依托单位:
国内基金
海外基金
新型滤波器综合技术-直接综合技术(Direct synthesis Technique)的研究及应用
  • 批准号:
    61671111
  • 项目类别:
    面上项目
  • 资助金额:
    58.0万元
  • 批准年份:
    2016
  • 负责人:
    肖飞
  • 依托单位: