EFRI C3 SoRo: Between a Soft Robot and a Hard Place: Estimation and Control Algorithms that Exploit Soft Robots' Unique Abilities

EFRI C3 SoRo:在软机器人和硬机器人之间:利用软机器人独特能力的估计和控制算法

基本信息

  • 批准号:
    1935312
  • 负责人:
  • 金额:
    $ 200万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-01-01 至 2024-12-31
  • 项目状态:
    已结题

项目摘要

This project will improve the ability to control fabric-reinforced inflatable soft robots. Soft robots offer tremendous promise because they can conform to features in an unknown environment and then change shape to perform tasks, such as entwining objects or squeezing into small gaps. These could be useful in search and rescue, disaster relief, and increasing customization in manufacturing. While scientists and engineers have managed to demonstrate these types of movements by trial and error, getting them to work under computer control has been difficult. Because soft robots are usually made of elastomeric materials, a multitude of sensors can be molded into the robot, measuring touch, proximity, and the shape of objects in the environment. With such a large number of sensors, the robot has access to a rich amount of data that can be used to help determine the current position and shape of the robot. The elastomeric material of soft robots also offers the opportunity to incorporate active materials that can change their properties upon command from a computer. These materials can be used to tune the stiffness of the soft robot or provide additional options for changing its shape. If successful, this research project will produce improved algorithms to process these sensor inputs so that the soft robot can distill them into meaningful information about itself and the world. The techniques will be leveraged to broadly spread the benefits of the research to the wider community. Teams of selected K-12 teachers will participate in a decathlon-style contest, using a single robot to compete in a series of diverse tasks and building their skills with soft robot technology for later use in their classrooms.The research effort centers around developing concise models for the motions of a fabric-reinforced rubber tube that can be evaluated quickly by a computer. Particular attention will be given to behaviors that are difficult to represent by existing techniques, such as wrinkling, pleating and buckling. Based on the simplified model, the algorithm will postulate a variety of possible shapes for the robot at each instant. The algorithm will then decide which is correct by comparing measurements from its many sensors to the predictions of the model. Using the data gathered by the robot platforms, the robot will be able to learn how to select the appropriate commands -- that is, the combinations of pneumatic valve signals and tunable stiffness patches in the rubber walls -- to autonomously complete useful tasks where the robot must push on the environment. The algorithm will be validated in representative tasks such as hanging drywall and retrieving objects in clutter.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.
该项目将提高控制织物增强充气软机器人的能力。软机器人提供了巨大的希望,因为它们可以在未知环境中适应特征,然后改变形状来执行任务,例如缠绕物体或挤进小间隙。这些可能在搜索和救援、救灾以及增加制造业的定制方面很有用。虽然科学家和工程师们已经成功地通过试验和错误来证明这些类型的运动,但让它们在计算机控制下工作一直很困难。由于软机器人通常由弹性材料制成,因此可以将大量传感器模制到机器人中,以测量环境中物体的触摸,接近度和形状。通过如此大量的传感器,机器人可以访问丰富的数据,这些数据可以用于帮助确定机器人的当前位置和形状。软机器人的弹性体材料还提供了结合活性材料的机会,这些活性材料可以根据计算机的命令改变其特性。 这些材料可用于调整软机器人的刚度或提供改变其形状的额外选项。如果成功,该研究项目将产生改进的算法来处理这些传感器输入,以便软机器人可以将它们提取为关于自身和世界的有意义的信息。将利用这些技术将研究的好处广泛传播给更广泛的社区。经过挑选的K-12教师组成的团队将参加十项全能比赛,使用一个机器人完成一系列不同的任务,并通过软机器人技术培养他们的技能,以便日后在课堂上使用。研究工作的重点是开发一种织物增强橡胶管运动的简明模型,这种模型可以通过计算机快速评估。将特别注意难以用现有技术表示的行为,如起皱、打褶和屈曲。基于简化的模型,该算法将假设机器人在每个时刻的各种可能的形状。然后,该算法将通过比较来自许多传感器的测量结果与模型的预测结果来决定哪一个是正确的。使用机器人平台收集的数据,机器人将能够学习如何选择适当的命令-即气动阀信号和橡胶壁中可调刚度补丁的组合-以自主完成机器人必须推动环境的有用任务。该算法将在代表性的任务中得到验证,例如悬挂石膏板和在杂物中检索物体。该奖项反映了NSF的法定使命,并通过使用基金会的智力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

期刊论文数量(14)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Modeling the dynamics of soft robots by discs and threads
通过圆盘和螺纹对软体机器人的动力学进行建模
Stretchable Optical Waveguide Sensor Suitability for Wrinkle Degree Detection in Soft Robots
Tractable and Intuitive Dynamic Model for Soft Robots via the Recursive Newton-Euler Algorithm
通过递归牛顿欧拉算法建立易于处理且直观的软体机器人动态模型
Soft Robot Shape Estimation: A Load-Agnostic Geometric Method
软机器人形状估计:一种与负载无关的几何方法
  • DOI:
    10.1109/iros55552.2023.10342225
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sorensen, Christian;Killpack, Marc D.
  • 通讯作者:
    Killpack, Marc D.
Pose Measurement and Contact Training of a Fabric-Reinforced Inflatable Soft Robot
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Joshua Schultz其他文献

Female Relief Systems in U.S. Military Fighter Ejection Seat Aircraft
美国军用战斗机弹射座椅飞机中的女性救援系统
A Compliant Rolling Ellipsoidal Thumb Joint for the TU Hand
TU 手的顺应滚动椭圆拇指关节

Joshua Schultz的其他文献

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{{ truncateString('Joshua Schultz', 18)}}的其他基金

MRI: Acquisition of a Lightweight 7-Axis Robotic Manipulator with Force Sensing for Archaeological and Engineering Research and Education
MRI:采购具有力感应功能的轻型 7 轴机器人操纵器,用于考古和工程研究与教育
  • 批准号:
    2216138
  • 财政年份:
    2022
  • 资助金额:
    $ 200万
  • 项目类别:
    Standard Grant
EAGER/Collaborative Research: Center-of-Mass Control for Expressive and Effective Movement in Bipedal Robots
EAGER/协作研究:双足机器人富有表现力和有效运动的质心控制
  • 批准号:
    1701378
  • 财政年份:
    2017
  • 资助金额:
    $ 200万
  • 项目类别:
    Standard Grant
Active Head Support for Children with Hypotonia
肌张力低下儿童的主动头部支撑
  • 批准号:
    1706428
  • 财政年份:
    2017
  • 资助金额:
    $ 200万
  • 项目类别:
    Continuing Grant
NRI: Multi-Digit Coordination by Compliant Connections in an Anthropomorphic Hand
NRI:通过拟人手中的兼容连接进行多数字协调
  • 批准号:
    1427250
  • 财政年份:
    2014
  • 资助金额:
    $ 200万
  • 项目类别:
    Standard Grant
CNIC: US-Belgium Engineering Planning Visit: Simplified Models for Bio-inspired Actuators
CNIC:美国-比利时工程规划访问:仿生执行器的简化模型
  • 批准号:
    1427787
  • 财政年份:
    2014
  • 资助金额:
    $ 200万
  • 项目类别:
    Standard Grant
SBIR Phase I: Development and Validation of an In Vitro Diagnostic of HDL Cholesterol Efflux and Coronary Artery Disease Risk
SBIR 第一阶段:HDL 胆固醇流出和冠状动脉疾病风险体外诊断的开发和验证
  • 批准号:
    1248683
  • 财政年份:
    2013
  • 资助金额:
    $ 200万
  • 项目类别:
    Standard Grant

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