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NRI: Collaborative Research: Unified Feedback Control and Mechanical Design for Robotic, Prosthetic, and Exoskeleton Locomotion

NRI: Collaborative Research: Unified Feedback Control and Mechanical Design for Robotic, Prosthetic, and Exoskeleton Locomotion
NRI:协作研究:机器人、假肢和外骨骼运动的统一反馈控制和机械设计
批准号:
1724464
负责人:
Aaron Ames
金额:
$53.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-01-01 至 2019-08-31

项目摘要

项目成果

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中文摘要
翻译
迫切需要可穿戴机器人,例如,假肢和外骨骼,改善行动不便的个人的生活质量-与人类用户共生的设备,以实现稳定,安全和有效的运动。 目前,由于中风、脊髓灰质炎、多发性硬化症、脊髓损伤和脑瘫的影响,美国约有470万人将受益于主动式下肢外骨骼,到2050年,估计美国将有150万人生活在严重的下肢截肢中。 然而,当前的可穿戴机器人设备不能满足这一不断增长的人口需求,因为它们体积庞大、笨重、噪音大,并且即使在短时间使用时也需要大电池,同时主要实现分层控制算法。 传统的设计-构建-测试方法昂贵且缓慢,忽略了硬件规格和控制算法性能之间的紧密耦合,阻碍了该领域的创新。 这项工作的愿景是提供一种方法--受到机器人运动进步的启发--通过机电和反馈系统的协同设计,允许下肢假肢和外骨骼满足现实世界的要求。 因此,这项工作的变革性质源于其实现可穿戴机器人的能力,这些机器人与人类协同工作,以提高移动性,为不断增长的机器人辅助设备行业提供模板,并可能改善数百万人的生活质量。 为了实现这项工作的愿景,总体研究目标是创建一个新的统一控制和设计框架,以实现机器人,假肢和外骨骼的高效和稳定运动。 这种控制方法的一个关键方面是能够通过(可穿戴)机器人设备、其环境和用户之间基于力的交互,以有效的方式在不同的目标之间进行调解,从而实现稳定性和安全性。由此产生的框架将通过具有严格设计要求的假肢和外骨骼的控制在环机械设计来利用,在新型人形机器人上进行实验测试,并通过人体试验进行临床评估。 因此,这项工作以下列具体目标为指导:(1)建立统一的在线优化控制框架,(2)在形式控制合成和满足严格性能要求的可穿戴机器人的机械设计之间创建反馈回路,(3)通过将控制器从两足人形机器人正式和实验性地转换为假肢和外骨骼来加速临床测试。 由于这些研究目标,这项工作有可能创造下一代机器人系统,使稳定,安全和有效的人类移动。
英文摘要
There is a pressing need for wearable robots, e.g., prostheses and exoskeletons, which improve the quality of life for individuals with limited mobility - devices that work symbiotically with human users to achieve stable, safe and efficient locomotion. At present, approximately 4.7 million people in the United States would benefit from an active lower-limb exoskeleton due to the effects of stroke, polio, multiple sclerosis, spinal cord injury, and cerebral palsy, and by 2050 an estimated 1.5 million people in the United States will be living with a major lower-limb amputation. Yet current wearable robotic devices do not address this growing population's needs since they are bulky, heavy, noisy, and require large batteries for even short duration use, while implementing predominately hierarchical control algorithms. Impeding innovation in this domain is the expensive and slow traditional design-build-test approach that ignores the tight coupling between hardware specifications and control algorithm performance. The vision of this work is to provide a methodology---inspired by advancements in robotic locomotion---that allows lower-limb prostheses and exoskeletons to meet real-world requirements through the co-design of the electromechanical and feedback systems. The transformative nature of this work, therefore, stems from its ability to realize wearable robots that synergize with humans to achieve increased mobility, providing a template for the growing robotic assistive device industry and potentially improving the quality of life of millions. To realize the vision of this work, the overarching research goal is to create a new unified control and design framework that will allow for the efficient and stable locomotion of robots, prostheses, and exoskeletons. A key aspect of this control methodology is the ability to continuously mediate between different objectives enforcing stability and safety in an efficient manner through force-based interactions among (wearable) robotic devices, their environment and the user. The resulting framework will be utilized via control-in-the-loop mechanical design of prostheses and exoskeletons with stringent design requirements, tested experimentally on a novel humanoid robot, and clinically evaluated through human subject trials. This work is, therefore, guided by the following specific goals: (1) develop a unified online optimization-based control framework for (wearable) robotic locomotion that efficiently mediates stability, safety and force constraints, (2) create a feedback loop between formal control synthesis and the mechanical design of wearable robots that satisfy stringent performance requirements, (3) accelerate clinical testing by translating controllers formally and experimentally from bipedal humanoid robots to prostheses and exoskeletons. As a result of these research goals, this work has the potential to create the next generation of robotic systems that enable stable, safe and efficient human mobility.
期刊论文(8)
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科研奖励(0)
会议论文
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits
基于人类偏好的外骨骼行走步态高维优化学习
DOI: 10.1109/iros45743.2020.9341416
发表时间: 2020
期刊: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS
影响因子: --
作者: [Tucker, Maegan, Cheng, Myra, Novoseller, Ellen, Cheng, Richard, Yue, Yisong, Burdick, Joel W., Ames, Aaron D.]
通讯作者: Ames, Aaron D.
Data-driven Characterization of Human Interaction for Model-based Control of Powered Prostheses
人类交互的数据驱动表征,用于基于模型的动力假肢控制
DOI: 10.1109/iros45743.2020.9341388
发表时间: 2020
期刊: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS
影响因子: --
作者: [Gehlhar, Rachel, Chen, Yuxiao, Ames, Aaron D.]
通讯作者: Ames, Aaron D.
A Scalable Safety Critical Control Framework for Nonlinear Systems
非线性系统的可扩展安全关键控制框架
DOI: 10.1109/access.2020.3025248
发表时间: 2020
期刊: IEEE Access
影响因子: 3.9
作者: [Gurriet, Thomas, Mote, Mark, Singletary, Andrew, Nilsson, Petter, Feron, Eric, Ames, Aaron D.]
通讯作者: Ames, Aaron D.
Towards Variable Assistance for Lower Body Exoskeletons
为下半身外骨骼提供可变辅助
DOI: 10.1109/lra.2019.2955946
发表时间: 2020
期刊: IEEE Robotics and Automation Letters
影响因子: 5.2
作者: [Gurriet, Thomas, Tucker, Maegan, Duburcq, Alexis, Boeris, Guilhem, Ames, Aaron D.]
通讯作者: Ames, Aaron D.
7
    Collaborative Research: Intelligent and Agile Robotic Legged Locomotion in Complex Environments: From Planning to Safety and Robust Control
    • 批准号:
      1923239
    • 项目类别:
      Standard Grant
    • 资助金额:
      $34.19万
    • 财政年份:
      2019
    • 负责人:
      Aaron Ames
    • 依托单位:
    CPS: Medium: Safety-Critical Cyber-Physical Systems: From Validation & Verification to Test & Evaluation
    • 批准号:
      1932091
    • 项目类别:
      Standard Grant
    • 资助金额:
      $119.92万
    • 财政年份:
      2019
    • 负责人:
      Aaron Ames
    • 依托单位:
    NRI: FND: COLLAB: Hierarchical Safe, and Distributed Feedback Control of Multiagent Legged Robots for Cooperative Locomotion and Manipulation
    • 批准号:
      1924526
    • 项目类别:
      Standard Grant
    • 资助金额:
      $37.5万
    • 财政年份:
      2019
    • 负责人:
      Aaron Ames
    • 依托单位:
    CPS: Frontier: Collaborative Research: Correct-by-Design Control Software Synthesis for Highly Dynamic Systems
    • 批准号:
      1724457
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $49.36万
    • 财政年份:
      2017
    • 负责人:
      Aaron Ames
    • 依托单位:
    海外基金