RI: Small: Collaborative Research: Evolutionary Approach to Optimal Morphology and Control of Transformable Soft Robots

RI：小型：协作研究：可变形软机器人的最佳形态和控制的进化方法

基本信息

批准号：
2008797
负责人：
Isuru Godage
金额：
$ 23万
依托单位：
DePaul 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：
2020-09-01 至 2023-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008797&HistoricalAwards=false
关键词：
RI Small Collaborative Research Evolutionary

项目摘要

The overall objective of the project is to leverage the principles of evolution in order to develop a new type of complex soft robots (robots that are constructed from compliant material) that can change their shape and mechanical properties to assume different forms in order to overcome environmental challenges such as uneven terrain. The motivation comes from the ways animals achieve efficient locomotion in their habitats by varying body shape and mechanical properties as a result of evolution over millions of years. Based on prior numerical results, the investigators hypothesize that highly adaptable locomotion can be achieved when given enough complexity in terms of shape deformation and mechanical properties. Current bioinspired soft robots, however, have limited capability to investigate such hypothesis. One key goal in this proposal is to develop innovative soft robotic platforms to study, for the first time, these numerical findings. The planned research has the potential to significantly enhance the functionality, adaptability, and versality of high-dimensional soft robots. The broader impact would be significant in several areas where soft robots have shown promise, particularly in inspection operations and search-and-rescue missions. The project is also expected to have a significant educational impact by engaging undergraduate students in the planned research activities and developing course content and new courses geared towards soft robots. Outreach efforts focus on workshops, public lectures, and engagements with elementary, middle, and high schools to foster collaborations with the local communities.The planned research is poised to unlock the evolutionary secrets of biological systems and open the door for the next generation of energy-efficient, adaptable, versatile, and human-friendly robots. To meet these goals, investigators propose to develop novel transformable and stiffness controllable soft robots and apply evolutionary computing to generate optimal morphological and stiffness trajectories for locomotion. The investigators employ evolutionary computing-based learning models to circumvent the curse of dimensionality associated with complex soft robotic systems and develop a comprehensive framework for developing optimal and robust control schemes and testing thereof using a series of rigorous experimental evaluations.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.

该项目的总体目标是利用进化原理来开发一种新型复杂的软机器人（由柔顺材料制成的机器人），它可以改变其形状和机械性能以呈现不同的形式，以克服环境的影响地形不平坦等挑战。其动机来自于动物在其栖息地中通过数百万年进化而改变的身体形状和机械特性来实现有效运动的方式。根据先前的数值结果，研究人员假设，当形状变形和机械性能方面具有足够的复杂性时，可以实现高度适应性的运动。然而，当前的仿生软机器人研究这种假设的能力有限。该提案的一个关键目标是开发创新的软机器人平台来首次研究这些数值发现。计划中的研究有可能显着增强高维软机器人的功能、适应性和通用性。在软机器人已显示出前景的几个领域，特别是在检查操作和搜救任务中，更广泛的影响将是重大的。该项目预计还将通过让本科生参与计划的研究活动以及开发针对软机器人的课程内容和新课程来产生重大的教育影响。外展工作的重点是研讨会、公开讲座以及与小学、初中和高中的接触，以促进与当地社区的合作。计划中的研究旨在解开生物系统的进化秘密，并为下一代能源打开大门-高效、适应性强、多功能且人性化的机器人。为了实现这些目标，研究人员建议开发新型可变形和刚度可控的软机器人，并应用进化计算来生成最佳的形态和刚度运动轨迹。研究人员采用基于进化计算的学习模型来规避与复杂软机器人系统相关的维数灾难，并开发了一个综合框架，用于开发最佳和鲁棒的控制方案，并使用一系列严格的实验评估对其进行测试。该奖项反映了 NSF 的法定使命通过使用基金会的智力优点和更广泛的影响审查标准进行评估，并被认为值得支持。