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Human-state based active physical human-robot interaction

Human-state based active physical human-robot interaction
基于人类状态的主动物理人机交互
批准号:
RGPIN-2022-03857
负责人:
Hu, Yue
金额:
$2.04万
依托单位:
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
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

项目摘要

项目成果

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中文摘要
翻译
在过去的十年中,协作机械手和辅助机器人设备的销售和采用都有所增加,这表明在工业应用和家庭环境中,人类与机器人并肩工作的应用正在发生转变。由于技术的快速发展,与机器人设备的物理交互将不可避免。机器人控制的研究主要集中在保证人身安全上,而往往忽视了人类使用者的心理安全和心理舒适。该项目旨在探索人类用户在控制机器人时的感知和心理舒适度,从精神和身体的角度实现真正安全的人机交互。拟定的研究计划包括以下目标:1。调查与机器人物理交互相关的感知,并确定相关因素(例如,接受度、心理负荷和交换力);2. 构建基于实时可测量数据的综合心理和身体状态的人类状态模型,同时考虑使用机器学习方法改进交互历史;3. 开发一种使用人-状态模型与用户交互的机器人自适应预测控制器,使控制结构分层,同时考虑人的状态、环境和任务完成情况;和4。为了在实际的机器人平台上验证结果,从协作机械手开始,协作机械手是世界上最先进的机器人,在加拿大大规模生产,加拿大公司如Kinova和在加拿大有生产基地的公司,如ABB, KUKA。这个研究项目是高度跨学科的,因为它包括社会机器人、机器人控制、人类建模、人为因素和机器学习等方面。滑铁卢大学(UW)的设施,包括RoboHub和运动捕捉实验室(MCL),将使该计划达到其既定目标,并有助于培养具有尖端技术的高技能专业人员。我们的学生将专攻人机交互,机器人控制,建模和机器学习,这些在机器人工业和机器人应用中发挥重要作用,如工业仓库组织,装配线,智能家居,护理行业,旨在提高加拿大人的生活质量。该项目培养的人才将为学术界和工业界的机器人技术进步做出贡献,这将确立加拿大在机器人技术新兴领域的世界领导者地位。
英文摘要
Collaborative manipulators and assistive robotic devices have increased in sales and adoption in the last decade, indicating a shift towards applications involving humans working side by side with robots, both in industrial applications and domestic environments. Physical interactions with robotic devices will become inevitable due to rapid advances in technology. Research on robot control has heavily focused on guaranteeing physical safety, but often ignores the psychological safety and mental comfort of the human user. This program intends to explore the perceptions and mental comfort of human users in the control of robots, enabling a truly safe human-robot interaction, from both the mental and physical points of view. The proposed research program consists of the following objectives: 1. To investigate the perceptions related to physical interactions with robots and to identify the relevant factors (e.g., acceptance, mental load, and exchanged forces); 2. To build a human-state model that is comprehensive of both mental and physical states based on real-time measurable data, considering also improvements in interaction history using machine learning methods; 3. To develop an adaptive and predictive controller for robots that uses the human-state model to interact with users, so that the control structure will be hierarchical and will consider at the same time the state of the human, the environment, and task completion; and 4. To validate the outcomes on actual robot platforms, starting with the collaborative manipulator, which is a state-of-the-art robot being produced worldwide and in Canada on a large scale, with Canadian companies such as Kinova and companies with production sites in Canada such as ABB, KUKA. This research program is highly interdisciplinary as it includes aspects of social robotics, robot control, human modeling, human factors, and machine learning. The facilities at the University of Waterloo (UW), including the RoboHub and the Motion Capture Lab (MCL) will permit this program to reach its defined objectives, and contribute to the training of highly skilled professionals with cutting--edge technology. Our students will become specialized in human-robot interaction, robot control, modeling, and machine learning, which play essential roles in the robotics industry and robotics applications, such as industrial warehouse organization, assembly lines, intelligent homes, care industry, aiming to improve the quality of life of Canadians. The trained personnel from this program will contribute to advancements in robotics in both academia and industry, which will establish the role of Canada as world leader in the rising field of robotic technologies.
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Human-state based active physical human-robot interaction
  • 批准号:
    DGECR-2022-00037
  • 项目类别:
    Discovery Launch Supplement
  • 资助金额:
    $0.91万
  • 财政年份:
    2022
  • 负责人:
    Hu, Yue
  • 依托单位:
国内基金
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  • 批准年份:
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  • 负责人:
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  • 项目类别:
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