High Performance, Intelligent and Efficient Robotic Systems: Performance Integration, Decomposition and System Hybridization

高性能、智能、高效的机器人系统：性能集成、分解与系统混合

• 批准号: RGPIN-2016-05030
• 负责人: Zhang, Dan
• 金额: $ 3.35万
• 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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689288
• 关键词: Performance; Intelligent; Efficient; Robotic; Systems

BACKGROUND: Robotics provides a transformative technology for manufacturing system in the 21st century. Effective use of robotics in manufacturing system is essential to future economic growth, job creation and global competitiveness. To meet the needs of the evolving manufacturing industry, robots must be faster, more accurate, better intelligence and more adaptable.****RESEARCH PROGRAM: In this research program, new methodologies for better intelligence, more resilience and adaptive robotic systems will be developed, the relationship between robot accuracy and speed will be examined and optimized, and the issue of performances integration for robotic system will be explored and a better strategy to design and control such system for advanced manipulation will be developed. The proposed research program involves the combination of two new paradigms: Performance Integration and Decomposition (PID) and System Hybridization (SH). The PID paradigm indicates the integration of system performances in conjunction with the decomposition of their structures. Thus, PID provides a strategy for resolving an apparent contradiction: while design and control tends to divide the system into subsystems or components that fulfill multiple functions or constraints, the subsystems must work together to perform these multiple functions. Furthermore, SH improves the robotic system performance by implementing hybrid mechanisms, hybrid optimization, and hybrid actuation. The SH approach synergistically integrates components to maximize their complementary strengths and minimize their weaknesses.****SIGNIFICANCE: The research can directly impact on the development of new theories and methodologies for next-generation robotic systems, which not only facilitate manufacturing but also promote other applications, such as robots for field rescue. The research will generate novel methodology for robotic system with better intelligence and resilience, and will bring economic benefits for the manufacturing industry by applying these new theories and methodologies. The results of the research program will provide a key insight for the development of higher performance robotic systems, and will positively impact the Canadian manufacturing economy by improving the performance and efficiency of many robotic products currently used in Canadian industries.**

背景：机器人技术为21世纪的制造系统提供了一种变革性的技术。在制造系统中有效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。为了满足不断发展的制造业的需求，机器人必须更快，更准确，更智能，适应性更强。研究报告：在这项研究计划中，将开发更好的智能，更具弹性和自适应的机器人系统的新方法，机器人精度和速度之间的关系将被检查和优化，机器人系统的性能集成问题将被探索，并将开发一个更好的策略来设计和控制这样的系统，以实现先进的操作。建议的研究计划涉及两个新的范式：性能集成和分解（PID）和系统杂交（SH）的组合。PID范例表明系统性能的集成与其结构的分解相结合。因此，PID提供了一种解决明显矛盾的策略：虽然设计和控制倾向于将系统划分为满足多个功能或约束的子系统或组件，但子系统必须一起工作以执行这些多个功能。此外，SH通过实施混合机制，混合优化和混合驱动来提高机器人系统的性能。SH方法协同整合各个组成部分，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：这项研究可以直接影响下一代机器人系统的新理论和方法的发展，这不仅有利于制造，而且还促进了其他应用，例如现场救援机器人。该研究将为机器人系统提供新的智能和弹性方法，并将通过应用这些新的理论和方法为制造业带来经济效益。该研究计划的结果将为开发更高性能的机器人系统提供关键见解，并将通过提高目前在加拿大工业中使用的许多机器人产品的性能和效率，对加拿大制造业经济产生积极影响。