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: 2314559
• 负责人: Joseph Najem
• 金额: $ 37.49万
• 依托单位: Pennsylvania State Univ University Park
• 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
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2314559&HistoricalAwards=false
• 关键词: Collaborative; Research; Embedded; Mechano; Intelligence

This Foundational Research in Robotics (FRR) award supports a collaborative research project that 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.

该机器人基础研究 (FRR) 奖项支持一项合作研究项目，该项目将创建具有集成传感器、互连、逻辑电路和执行器的软材料。这些材料将使软机器人的开发成为可能，其感知、处理和响应能力分布在整个结构中。这些功能将通过一个软机器人平台来展示，该平台可以仅使用这些新颖的材料，根据形状、大小和重量来识别和分类简单的物体，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新型软机器人组件的第一步，该组件可以协调并智能地与环境中的物体交互，以实现一系列实际目的。此类设备代表了软机器人领域的重要一步，并将广泛推进运动控制系统、自主触觉设备、自我感知传感器执行器网络等的未来。制造、运输和生物医学设备等对社会重要的应用领域可能会受到潜在影响。该研究将与广泛的外展、教育和指导计划相结合，将研究概念融入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在软件中建立材料和功能组件的基本综合。体现智能的重要性，赋予机器人新的功能，与严重依赖附加硬件的当前系统相比，这些功能将显着增强其自主性。 与现有系统相比，新系统将需要更少的电力，反应更快，生存能力更好。 该项目将最终开发出一款软机器人分拣操纵器，该操纵器能够自动检测物品的物理特征，并将这些物品放置在具有相似特征的物体附近。这一目标将通过嵌入式机械智能和场响应聚合物的新颖集成来实现。这些组成部分将共同处理有关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中。由于仅需要低压输入即可运行，嵌入式机械智能仅采用必要的计算能力，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驱动权限。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进行评估，被认为值得支持以及更广泛的影响审查标准。