CAREER: Adaptive Actuation and Control in Embodied Biohybrid Robots

职业：生物混合机器人的自适应驱动和控制

基本信息

批准号：
2044785
负责人：
Victoria Webster-Wood
金额：
$ 60万
依托单位：
Carnegie-Mellon University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2026-03-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2044785&HistoricalAwards=false
关键词：
CAREER Adaptive Actuation Control Embodied

项目摘要

Animals are often a source of inspiration in robotic design. By designing from animal blueprints, engineers can create robotic systems capable of walking, running, crawling, swimming, and even flying. However, even with the advances in robotics over the past decades, robotic systems still fall short of many of the capabilities seen in biological animals. One key difference between existing robots and their animal counterparts is that biological systems are made up of soft, adaptable materials, including muscles for actuation and neurons for control. This CAREER award investigates how to fabricate robust, adaptable actuators for biohybrid robots using living muscle, how these actuators adapt to exercise, and how to control biohybrid robots with living neurons. Additionally, this CAREER award supports educational and outreach initiatives to improve recruitment and retention of diverse students and faculty in robotics and STEM. Accessible age-appropriate educational materials based on the research outcomes will be developed, made available to middle and high school teachers, and integrated into a graduate course on Bioinspired Robotics. The research team will host virtual and in-person outreach events to introduce students to bioinspired and biohybrid robotics. Underrepresented undergraduate students will be recruited for summer research experiences in biohybrid robotics and modeling. Finally, the investigator will promote tools for recruitment and retention of women faculty in robotics. This 5-year CAREER project will result in bioactuators capable of interfacing with a range of robotic structures via tendon-like interfaces, bioinspired neural networks for bioactuator control, and the ability to perform basic ‘programming’ of biohybrid robots. Biohybrid robotics directly harnesses living tissues as renewable engineering materials. In particular, muscle-based bioactuators are self-healing, compliant, and adapt to loading. Whereas most biohybrid research to date has focused on biological materials as individual components of the system, approaches for the integrated design, fabrication, and ‘programming’ of robust bioactuators and biological control networks are needed to improve biohybrid robot performance and broaden applicability. To meet this need, this CAREER project will (1) enable adaptive bioactuation of a wide range of robotic peripheries through the creation of embedded biocompatible interfaces, (2) model and fabricate simple biological neural networks to control bioactuators, and (3) train integrated bioactuators and biological neural networks. Not only will the proposed research approach lead to advances in bioactuation and control, but it will also specifically focus on integrated biohybrid robot development. ‘Programmable’ biohybrid robots have applications in medicine where small-scale biocompatible systems could be used as self-actuating stents or medical implants, or as functional components of neuromuscular tissues-on-a-chip for drug-screening and neuroscience. The proposed research lays the foundation for addressing future challenges in biohybrid robotics, including integrating diverse sensing modalities into biohybrid robot systems, understanding the effect of embodiment on neuromuscular control circuits, and studying emergent dynamics in distributed biohybrid actuation systems. The research approach in this CAREER proposal will be integrated with an educational and outreach plan to (1) incorporate neuromuscular modeling in biohybrid robotics curriculum, (2) improve retention of diverse students in robotics through biohybrid robot experiences, and (3) build tools to improve visibility of women faculty in robotics towards improving retention.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.

动物通常是机器人设计的灵感来源，通过根据动物蓝图进行设计，工程师可以创建能够行走、奔跑、爬行、游泳甚至飞行的机器人系统。现有机器人及其动物伙伴之间的许多功能仍然存在不足，因为生物系统是由柔软的、适应性强的材料组成，包括用于驱动的肌肉和用于控制的神经元。如何制造坚固的，使用活体肌肉的生物混合机器人的适应性执行器，这些执行器如何适应运动，以及如何控制具有活体神经元的生物混合机器人。此外，该职业奖支持教育和推广计划，以改善机器人和 STEM 领域多样化学生和教师的招募和保留。将根据研究成果开发适合年龄的教育材料，提供给初中和高中教师，并将其纳入仿生机器人学研究生课程中。向学生介绍生物启发和生物混合机器人的外展活动将招募代表性不足的本科生进行生物混合机器人和建模方面的夏季研究经验。将产生能够通过类腱接口与一系列机器人结构连接的生物执行器、用于生物执行器控制的仿生神经网络以及执行生物混合的基本“编程”的能力生物混合机器人直接利用活体组织作为可再生工程材料，特别是，基于肌肉的生物致动器具有自我修复、顺应性和适应负载的能力，但迄今为止大多数生物混合研究都集中在作为系统的单独组件的生物材料上。需要对稳健的生物执行器和生物控制网络进行集成设计、制造和“编程”的方法来提高生物混合机器人的性能并扩大适用性，为了满足这一需求，该职业项目将。 (1) 通过创建嵌入式生物相容性接口实现各种机器人外围设备的自适应生物驱动，(2) 建模和制造简单的生物神经网络来控制生物驱动器，(3) 训练集成生物驱动器和生物神经网络。所提出的研究方法会带来生物驱动和控制方面的进步，但它也将特别关注集成的“可编程”生物混合机器人的开发，该机器人在小型生物相容性系统可能的医学领域有应用。用作自动支架或医疗植入物，或用作药物筛选和神经科学的神经肌肉组织芯片的功能组件，为解决生物混合机器人技术的未来挑战奠定了基础，包括将不同的传感方式集成到其中。生物混合机器人系统，了解实施例对神经肌肉控制电路的影响，并研究分布式生物混合驱动系统中的紧急动力学。本职业提案中的研究方法将与教育和推广相结合。计划（1）将神经肌肉建模纳入生物混合机器人课程，反映出，（2）通过生物混合机器人体验提高不同学生对机器人技术的保留率，以及（3）构建工具来提高女性教师在机器人技术领域的知名度，从而提高保留率。该奖项 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。