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CAREER: Dynamic Modeling and Fabrication of Compliant Material Systems for On-Demand Specialist Robots

职业：按需专业机器人的合规材料系统的动态建模和制造

基本信息

批准号：
1944789
负责人：
Daniel Aukes
金额：
$ 67.8万
依托单位：
Arizona State University
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：
2020-07-01 至 2025-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1944789&HistoricalAwards=false
关键词：
CAREER Dynamic Modeling Fabrication Compliant

项目摘要

This Faculty Early Career Development (CAREER) grant will make it possible to develop cost-effective, “specialist” robots that can be prototyped by a non-expert in a matter of hours. The goal of this project is to make robots more ubiquitous, accessible, and tunable for newcomers to robotics and for applications in industry, education, and academic research. Achieving this goal requires a shift towards more affordable materials, accessible fabrication strategies, and assistive design software that considers the particular dynamics of cost-efficient motors and materials, as well as the needs of specific applications. The results of this project will impact fields in which specialization is desirable, such as assistive robotics for the elderly, custom agricultural applications, and trash pickup in smart cities. The robots developed through this project will also serve as an affordable starting point for children to compete in after-school robotics competitions organized by local, youth-focused nonprofits. In addition, the models and templates developed for this project will be integrated into college-level robotics curricula, permitting students to venture deeper into advanced robotics topics earlier in their studies.The fundamental research contribution of this project lies within the consideration and integration of compliant material systems into a unified design framework that supports the specialization and optimization of dynamical robotic systems. The research plan involves developing reduced models for the nonlinear mechanics of material systems that permit more affordable robot designs, and considering that compliance in simulations to customize, model, and optimize their performance. This approach will investigate machine learning techniques to automatically tune parametric, template-driven designs in a way that balances competing performance trade-offs like speed, payload, and efficiency. The project’s research objectives include the representation of compliance, the utilization and understanding of compliance, the optimization of compliant systems, and validation of the framework through prototyping, experimental validation, and exemplar use-cases. The generality of the approach will be demonstrated by modeling and optimizing several subsystems of a bipedal robot.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.

这项教师早期职业发展（Career）资助将使开发具有成本效益的“专家”机器人成为可能，非专业人员可以在几小时内制作出原型。该项目的目标是使机器人更加无处不在、易于使用和可调，使机器人新手能够在工业、教育和学术研究中应用。实现这一目标需要转向更经济实惠的材料，可访问的制造策略，以及辅助设计软件，考虑具有成本效益的电机和材料的特定动态，以及特定应用的需求。该项目的成果将影响需要专业化的领域，如老年人辅助机器人、定制农业应用和智能城市的垃圾收集。通过这个项目开发的机器人也将作为一个负担得起的起点，让孩子们参加由当地以青年为重点的非营利组织组织的课后机器人比赛。此外，为这个项目开发的模型和模板将被整合到大学水平的机器人课程中，允许学生在学习的早期更深入地探索高级机器人主题。该项目的基础研究贡献在于考虑并将柔性材料系统集成到一个统一的设计框架中，该框架支持动态机器人系统的专业化和优化。研究计划包括为材料系统的非线性力学开发简化模型，使机器人设计更加经济实惠，并考虑到仿真中的合规性，以定制，建模和优化其性能。这种方法将研究机器学习技术，以平衡速度、有效载荷和效率等竞争性能权衡的方式自动调整参数化、模板驱动的设计。该项目的研究目标包括法规遵循的表示、法规遵循的利用和理解、法规遵循系统的优化，以及通过原型、实验验证和范例用例来验证框架。该方法的通用性将通过建模和优化双足机器人的几个子系统来证明。该奖项反映了美国国家科学基金会的法定使命，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。