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.

机器人操作员将在非结构化的人类和空间环境中执行日益复杂的操作任务，这就要求机器人控制技术和机器人智能的进步。随着机器人越来越希望与人类互动、协助、服务和探索，新的研究挑战出现了。在应对这些挑战时，具有多种工作模式的智能机器人操作手是必不可少的。随着机器人继续在工作中与人类相辅相成，从驱动、传感和控制方面来说，安全一直是机器人设计中的一个关键问题。根据机器人操作方面的最新研究进展，拟议研究计划的长期愿景是开发智能机器人系统，以便在非结构化的人类和空间环境中进行高效和安全的机器人操作。这将涉及开发具有能力的智能控制系统的创新机器人操作器。针对这一长期目标，在我们最新研究成果的基础上，定义了以下短期目标：1)通过推广我们提出的多工作模式(MWM)机器人控制方法，分类并适应与非结构化环境相关的模型误差，开发机器人操作控制框架；2)通过将所提出的MWM机器人控制方法与机器学习技术相融合，发展机器人智能，以处理具有环境模型不准确性和实时变化的复杂机器人操作任务；3)将MWM控制方法扩展到机器人捕获空间中的未知目标，应用最近发展的关节力矩估计和尖端位置测量方法；4)进一步开发我们的弹簧辅助模块化可重构机器人和控制系统，以实现灵活和安全的多种工作模式和机器人智能操作，并考虑到诸如能源效率和带有弹簧和离合器机构的紧急制动等实际问题；以及5)开发用于多种工作模式的智能机器人操作器创新编程的软件，以满足复杂操作任务。拟议的研究计划将产生创新而实用的智能机器人系统设计和控制技术，用于在非结构化的人类或空间环境中执行复杂的操作，产生高质量的研究成果，并为实际的机器人操作问题提供有效的解决方案。能够在非结构化环境中有效操作的机器人系统将在服务、健康、先进制造和空间探索等领域获得巨大应用，带来巨大的商业潜力。此外，由于其多学科性质，拟议的研究计划将对加拿大高素质人才的培训做出重大贡献。