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

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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.