CAREER: Muscle-Inspired Load-Adaptive Actuation for Compliant Robotics

职业：针对顺应性机器人的受肌肉启发的负载自适应驱动

• 批准号: 1845203
• 负责人: Matthew Bryant
• 金额: $ 50万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1845203&HistoricalAwards=false
• 关键词: CAREER; Muscle; Inspired; Load; Adaptive

This Faculty Early Career Development Program (CAREER) project will advance the national health, welfare, and security through scientific advancements in the field of biologically-inspired robotics favorable for wearable technology and exoskeletons. The research will make important contributions to society by increasing robot energy efficiency and performance while simultaneously improving human-robot interaction compatibility and safety through the use of inherently soft actuators. Actuators are critical component of a machine or robot that are responsible for moving and controlling a mechanism or components of a system. Current robotic actuators are poorly suited to wearable or human-assistive applications because they are inefficient when used in slow, variable-speed motions like moving an arm or leg. In addition, they create human safety hazards due to their stiffness and rigid motions. This research will create a new type of actuator that is inspired by human muscle tissues, which contain thousands of fibers that are selectively recruited to provide only the amount of force needed for a given task. Engineering artificial muscles to incorporate this concept of selective recruitment will allow the robot to consume less energy, therefore increasing battery life and range. It will also allow the same actuator to generate both gentle, precise motion as well as high-force, high-speed motion, depending on the task, while also incorporating soft construction and controllable stiffness. This new approach will help make assistive robotics safer, more comfortable, and more compatible with human physiology, all of which will provide more rapid and effective recovery for those suffering from debilitating injuries or disabilities. This research lends itself well to outreach opportunities to work with young people who suffer from disabilities; the outreach activities will help inspire them and show them how engineering can be used to improve their lives and the lives of those around them.Improvements in actuator efficiency and performance can be made by implementing the biologically-inspired concept of orderly recruitment to create an integrated fluidic artificial muscle tissue that contains selectable actuation elements of different sizes. This tissue can dynamically adapt to changes in load by recruiting different combinations of actuators. This orderly recruitment scheme conserves energy by reducing working fluid consumption and minimizing throttling losses. It also allows for a wide gamut of force generation and fast response time due to reduced flow rate demand. The goals of this research are to (1) understand the relationships between recruitment state, pressure, force, contraction, and velocity for selective-recruitment fluidic artificial muscle tissues; (2) establish the effects of topology on performance and create a framework for optimizing tissues to robot operating tasks and requirements; (3) understand implications of recruitment control architecture; and (4) demonstrate bandwidth improvements, variable compliance, and energetic savings on a walking robot platform.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个教师早期职业发展计划（CAREER）项目将通过有利于可穿戴技术和外骨骼的生物启发机器人领域的科学进步来促进国家健康，福利和安全。该研究将通过提高机器人的能源效率和性能，同时通过使用固有的软致动器提高人机交互的兼容性和安全性，为社会做出重要贡献。执行器是机器或机器人的关键部件，负责移动和控制系统的机构或部件。目前的机器人致动器不太适合可穿戴或人类辅助应用，因为它们在缓慢的变速运动（如移动手臂或腿）中使用时效率低下。此外，由于它们的刚度和刚性运动，它们会造成人身安全危险。这项研究将创造一种受人类肌肉组织启发的新型致动器，其中包含数千种纤维，这些纤维被选择性地招募，仅提供给定任务所需的力。将这种选择性招募的概念融入人工肌肉工程中，将使机器人消耗更少的能量，从而增加电池寿命和范围。它还将允许同一个致动器根据任务产生温和、精确的运动以及高力、高速的运动，同时还结合了软结构和可控的刚度。这种新方法将有助于使辅助机器人更安全，更舒适，更符合人体生理学，所有这些都将为那些遭受衰弱伤害或残疾的人提供更快速，更有效的康复。这项研究很适合提供与残疾年轻人合作的外展机会;外展活动将有助于启发他们，并向他们展示如何利用工程学来改善他们和周围人的生活。通过实施生物-有序募集的灵感概念，以产生包含不同尺寸的可选择致动元件的集成流体人造肌肉组织。该组织可以通过招募不同的致动器组合来动态地适应负载的变化。这种有序的补充方案通过减少工作流体消耗和最小化节流损失来节省能量。它还允许广泛的力产生和快速响应时间，由于降低流速的需求。本研究的目的是：（1）了解选择性募集流体人工肌肉组织的募集状态、压力、力、收缩和速度之间的关系;（2）建立拓扑结构对性能的影响，并建立一个优化组织以满足机器人操作任务和要求的框架;（3）了解募集控制结构的含义;以及（4）在步行机器人平台上展示带宽改进、可变顺应性和能量节省。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Modeling of Resistive Forces and Buckling Behavior in Variable Recruitment Fluidic Artificial Muscle Bundles

• DOI: 10.3390/act10030042
• 发表时间: 2021-03-01
• 期刊: ACTUATORS
• 影响因子: 2.6
• 作者: Kim, Jeong Yong;Mazzoleni, Nicholas;Bryant, Matthew
• 通讯作者: Bryant, Matthew

Motor unit buckling in variable recruitment fluidic artificial muscle bundles: implications and mitigations

可变招募流体人工肌束中的运动单位屈曲：影响和缓解

• DOI: 10.1088/1361-665x/ac49d9
• 发表时间: 2022
• 期刊: Smart Materials and Structures
• 影响因子: 4.1
• 作者: Mazzoleni, Nicholas;Kim, Jeong Yong;Bryant, Matthew
• 通讯作者: Bryant, Matthew

Free strain gradient reversal of a variable recruitment fluidic artificial muscle bundle

可变募集流体人工肌束的自由应变梯度反转

• DOI: 10.1117/12.2583213
• 发表时间: 2021
• 期刊: and Bioreplication XI
• 作者: Kim, Jeong Yong;Mazzoleni, Nicholas;Bryant, Matthew
• 通讯作者: Bryant, Matthew

Control of a dynamic load emulator for hardware-in-the-loop testing of fluidic artificial muscle bundles

用于流体人工肌束硬件在环测试的动态负载模拟器的控制

• DOI: 10.1117/12.2612920
• 发表时间: 2022
• 期刊: and Bioreplication XI
• 作者: Mazzoleni, Nicholas;Kim, Jeong Yong;Bryant, Matthew J.
• 通讯作者: Bryant, Matthew J.

Implications of Spatially Constrained Bipennate Topology on Fluidic Artificial Muscle Bundle Actuation

• DOI: 10.3390/act11030082
• 发表时间: 2022-03
• 期刊: Actuators
• 影响因子: 2.6
• 作者: Emily Duan;M. Bryant