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: York University
• 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
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760319
• 关键词: Structural; Synthesis; Performance; Study; Generalized

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.

背景：机器人技术通过节省成本、提高产品质量和工作条件，彻底改变了制造业。在制造业中继续有效使用机器人技术对于未来的经济增长、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的趋势是使用称为传统并联机械手（CPM）的机器人。与串联机械手相比，CPM具有更高的刚度、精度和负载能力。尽管有这些优势，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，尚未被行业广泛采用。 研究报告：拟议的研究计划侧重于下一代并联机器人-广义并联机器人（GPMs）-可以克服CPM的局限性，更快，更准确地执行任务，具有更大的工作空间和更大的适应性，以不断变化的工作任务和条件。长期目标是开发用于结构合成的GPMs的设计方法，开发用于改善GPMs性能的理论，并通过专注于关键技术差距和严格的实验，将这些技术转移到工业应用中。短期目标是研究和开发：（1）具有可配置平台的GPMs，以提高任务适应性;（2）具有耦合子链的GPMs，以提高刚度;（3）具有铰接移动平台的GPMs，以实现更大的工作空间;以及4）可重新配置的GPMs，以提高性能。我们将使用两个新的范例：性能设计（DFP）和系统集成（SI）开发新的设计方法和技术的高性能GPMs。DFP范式生成一个集成环境，使机器人结构的设计和开发的最佳系统性能的同时。SI方法以协同方式整合各个组成部分，以最大限度地发挥其互补优势，并最大限度地减少其弱点。 重要性：该研究计划将为下一代GPMS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时间，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日益增长的需求。