EAGER: Controlled Pulsed-Combustion-Based Actuation for Soft Robots

这个早期概念探索性研究资助（EAGER）项目探索了使用燃烧为软机器人提供动力。与具有相同能量的电池相比，化学燃料使用的质量和体积要小得多，并且燃烧可以用来产生巨大的力量。然而，基于燃烧的系统比机电解决方案的成熟度低得多。这个高风险项目将有助于实现由快速化学反应提供动力的软机器人的三个关键要素：1）机器人动力学模型，2）致动器的设计框架，以及3）用于获得所需运动的控制合成理论。该项目将通过创造用于搜索和救援以及环境监测等应用的低成本软机器人来促进国家福利。创造快速，强大和自主的软机器人，能够执行复杂和精确的任务，需要发明新的驱动和控制方法。为了实现这一愿景，该项目将引入一种基于系统和控制的方法，用于开发由自主脉冲燃烧动力软模块组成的可控模块化机器人，能够以高速施加大的周期性力。这一目标将通过以下方式实现：采用新的方法来控制用于致动的脉冲爆炸，使用和改进用于控制脉冲燃烧驱动的软致动器的现代和最佳技术，和新的真实的发展-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，被认为值得支持和更广泛的影响审查标准。

This EArly-concept Grant for Exploratory Research (EAGER) project explores the use of combustion to power soft robots. Chemical fuels use much less mass and volume compared to batteries with the same energy, and combustion can be used to generate large forces. However, combustion-based systems are at a much lower state of maturity than electromechanical solutions. This high-risk project will contribute to three key elements for the realization of soft robots powered by rapid chemical reactions: 1) a model for the robot dynamics, 2) a design framework for the actuators, and 3) a theory of control synthesis for obtaining desired motions. This project will advance the national welfare by enabling the creation of low-cost soft robots for applications such as search and rescue and environmental monitoring. The creation of fast, powerful and autonomous soft robots, capable of performing complex and precise tasks, requires the invention of new actuation and control methods. In order to achieve this vision, this project will introduce a systems-and-control-based methodology for the development of controllable modular robots composed of autonomous pulsed-combustion-powered soft modules, capable of exerting large periodic forces at high speeds. This objective will be achieved by introducing new approaches for the control of pulsed explosions for actuation, the use and advancement of modern and optimal techniques for the control of pulsed-combustion driven soft actuators, and the development of new real-time methods for the control of modular soft robots.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.