课题基金 / 基金详情

Collaborative Research: Embedded Mechano-Intelligence for Soft Robotics

Collaborative Research: Embedded Mechano-Intelligence for Soft Robotics
合作研究:软机器人的嵌入式机械智能
批准号:
2314560
负责人:
Kon-Well Wang
金额:
$45.4万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2026-08-31

项目摘要

项目成果

Kon-Well Wang的其他基金

相似基金

相关文献

中文摘要
翻译
这个合作的机器人基础研究(FRR)项目将创造具有集成传感器、互连、逻辑电路和致动器的软材料。这些材料将使软机器人的开发具有感知、处理和响应性分布在其结构中。这些能力将通过一个软机器人平台来展示,该平台可以根据简单对象的形状、大小和重量进行识别和分类,只使用这些新材料,而不需要任何额外的传感或计算。这种基于软材料的机械手将是迈向一种新型软机器人部件的第一步,这种部件可以协调并智能地与环境中的物体接触,用于一系列实际目的。这些设备代表着软机器人领域的重要一步,并将广泛地推动运动控制系统、自主触觉设备、自我感知传感器-执行器网络等的未来。在制造、运输和生物医学设备等具有重要社会意义的应用领域,可能会感受到潜在的影响。这项研究将与广泛的外展、教育和指导计划相结合,将研究概念整合到课堂和多个不同学生群体的参与活动中。该项目的研究目标是建立软物质中材料和功能组件的基本合成,以体现智能,赋予机器人新的能力,与目前严重依赖附加硬件的系统相比,这些能力将显著增强机器人的自主性。与现有系统相比,新系统需要的电力更少,反应更快,生存能力更强。这个项目最终将是一个软机器人分拣操纵器,它自动检测物品的物理特征,并将这些物品定位到与具有相似特征的物体接近的位置。这一目标将通过嵌入式机械智能和场响应型聚合物的新型集成来实现。这些组件将一起处理关于物品形状和重量的信息,并将触发操纵器的重新配置,以便将物品定位到不同的类别。由于只需要低电压输入就能工作,嵌入式机械智能只需使用必要的计算能力,并消除了传统控制器和软材料中容易出现故障的电线。场响应型聚合物将与弹性稳定性理论原理结合使用,以最大限度地减少重新配置承载机械手所需的执行权限。该奖项反映了NSF的法定使命,并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This collaborative Foundational Research in Robotics (FRR) project will create soft materials with integrated sensors, interconnections, logic circuits, and actuators. These materials will enable the development of soft robots with perception, processing, and responsiveness distributed throughout their structures. These capabilities will be demonstrated by a soft robotic platform that can recognize and sort simple objects by their shape, size, and weight, using only these novel materials and without requiring any additional sensing or computing. This soft material-based manipulator will be the first step towards a new class of soft robotic components that can coordinate and intelligently engage with objects in their environment, for a range of practical purposes. Such devices represent a major step for the field of soft robotics and will broadly advance the future of motion control systems, autonomous haptic devices, self-aware sensor-actuator networks, and more. Potential impacts may be felt in societally important application areas such as manufacturing, transportation, and biomedical devices. The research will be coupled with an extensive outreach, education, and mentoring program that integrates the research concepts into classroom and engagement activities among multiple diverse student groups.The research goal of this project is to establish a fundamental synthesis of material and functional components in soft matter to embody intelligence, endowing robots with new capabilities that will significantly enhance their autonomy as compared to the current systems that heavily depend on add-on hardware. The new system will require less electric power and have faster reactions and better survivability than current systems. This project will culminate in a soft robotic sorting manipulator that autonomously detects physical characteristics of items and positions those items into proximity with objects having similar features. This goal will be achieved by a novel integration of embedded mechano-intelligence and field-responsive polymers. Together, these constituents will process information regarding item shape and weight and will trigger reconfiguration of the manipulator so as to position the items into distinct categories. By requiring only a low-voltage input to function, the embedded mechano-intelligence employs only the necessary computational power and eliminates conventional controllers and failure-prone electrical wiring in soft materials. The field-responsive polymers will be used in conjunction with principles of elastic stability theory to minimize the actuating authority required to reconfigure the load-bearing manipulator.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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Collaborative Research: Understanding and Harnessing Complex Dynamics of Coupled Mechanical-Electrical System for an Improved Vibration Energy Harvesting
Collaborative Research: Frequency Selective Structures for High Sensitivity/High Resolution Damage Identification via Impediographic Tomography
EFRI-BSBA: Learning from Plants -- Biologically-Inspired Multi-Functional Adaptive Structural Systems
SST - Multifunctional Adaptive Piezoelectric Sensory System for Structural Damage Detection
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)