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: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=615453
• 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。机器人技术在制造系统中的有效应用对未来经济增长、创造就业机会和提高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、更精确、更好的智能和更强的适应性。