Develop Intelligent Robot Systems for Efficient and Safe Robotic Manipulations in Unstructured Human and Space Environments

开发智能机器人系统，在非结构化人类和空间环境中进行高效、安全的机器人操作

• 批准号: RGPIN-2022-03807
• 负责人: Liu, Guang
• 金额: $ 2.84万
• 依托单位: Ryerson 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=743246
• 关键词: Develop; Intelligent; Robot; Systems; Efficient

Robot manipulators are expected to execute manipulation tasks of increased complexity in unstructured human and space environments, which calls for advancement in robot control techniques and robot intelligence. New research challenges emerge as robots are increasingly desirable to interact, assist, serve, and explore with humans. In tackling these challenges, intelligent robot manipulators with multiple working modes are essential. As robots continue to complement humans in their work, safety has been a critical concern in robot design in terms of actuation, sensing and control. In line with the most recent research advancements on robotic manipulation, the long-term vision of the proposed research program is to develop intelligent robot systems for efficient and safe robotic manipulations in unstructured human and space environments. This will involve the development of innovative robot manipulators with capable intelligent control systems. Aiming at this long term objective, and building upon our recent research achievements, the following short-term objectives are defined: 1) develop a framework for robot manipulation control by generalizing our proposed multiple working mode (MWM) robot control approach, categorizing and accommodating model inaccuracies associated with unstructured environments; 2) develop robot intelligence by fusing the proposed MWM robot control approach with machine learning techniques for complicated robotic manipulation tasks with environment model inaccuracy and real-time variation; 3) extend the MWM control approach to robotic capture of unknown targets in space, applying the recently developed methods for joint torque estimation and tip position measurement; 4) further develop our spring assisted modular and reconfigurable robot and control system for dexterous and safe manipulations with multiple working modes and robot intelligence, with consideration of practical issues such as energy efficiency and emergency braking with a spring and clutch mechanism; and 5) develop software for innovative programming of intelligent robot manipulators with multiple working modes for complicated manipulation tasks. The proposed research program will generate innovative yet practical techniques of design and control of intelligent robotic systems for performing complex manipulations in unstructured human or space environments, generating high quality research contributions and providing effective solutions to practical robotic manipulation problems. Robot systems capable of manipulating effectively in unstructured environments will find tremendous applications in sectors such as service, health, advanced manufacturing and space exploration, leading to huge commercialization potentials. Furthermore, with its multidisciplinary nature, the proposed research program will contribute significantly to training of highly qualified personnel for Canada.

预计机器人操纵器将执行非结构化的人和太空环境中增加复杂性的操纵任务，该任务要求在机器人控制技术和机器人智能中进步。随着机器人越来越希望与人类互动，协助，服务和探索，新的研究挑战。在应对这些挑战时，具有多种工作模式的智能机器人操纵器至关重要。随着机器人在工作中继续补充人类，在驱动，感应和控制方面，安全性是机器人设计的关键问题。与最新的机器人操作研究进步一致，该计划的研究计划的长期愿景是开发智能机器人系统，以在非结构化的人类和空间环境中开发有效且安全的机器人操作。这将涉及具有能力智能控制系统的创新机器人操纵器的开发。针对这个长期目标，并基于我们最近的研究成就，定义了以下短期目标：1）通过推广我们建议的多重工作模式（MWM）机器人控制方法，对机器人操纵控制的框架开发一个框架，对与非结构环境相关的模型进行分类和适应模型； 2）通过将提议的MWM机器人控制方法与机器学习技术融合在一起，以与环境模型的不准确性和实时变化相融合来开发机器人智能； 3）将MWM控制方法扩展到空间中未知靶标的机器人捕获，采用最近开发的接头扭矩估计和尖端位置测量的方法； 4）进一步开发了我们的弹簧辅助模块化和可重构机器人和控制系统，用于具有多种工作模式和机器人智能的灵巧和安全操作，并考虑了实用问题，例如能源效率和紧急制动，并具有弹簧和离合器机制； 5）开发用于具有多种工作模式的智能机器人操纵器的创新编程软件，用于复杂的操纵任务。拟议的研究计划将生成智能机器人系统设计和控制的创新但实用的技术，以在非结构化的人类或太空环境中进行复杂的操作，从而产生高质量的研究贡献，并为实践机器人操纵问题提供有效的解决方案。能够在非结构化环境中有效操纵的机器人系统将在服务，健康，高级制造和太空勘探等领域找到巨大的应用，从而带来巨大的商业化潜力。此外，凭借其多学科的性质，拟议的研究计划将为加拿大的高素质人员培训做出重大贡献。