Collaborative Research: Plant-Inspired Growing Robots Operating in Multiple Time Scales

协作研究：在多个时间尺度上运行的植物启发种植机器人

• 批准号: 2312422
• 负责人: Suyi Li
• 金额: $ 50.17万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2312422&HistoricalAwards=false
• 关键词: Collaborative; Research; Plant; Inspired; Growing

This award supports fundamental research to create plant-inspired robots for long-duration monitoring missions in congested and dynamically evolving environments. Such environments abound in our world, for example, urban shopping districts, tropical forests, underwater reefs, and undeveloped islands. These locations are typically inaccessible and resource-limited for human operations, and they evolve slowly but substantially over time (e.g., propagating vegetation). However, “being right there” in these environments and responding to events at multiple time scales is critical, especially for environmental protection. Therefore, in this project plant-inspired robots will be designed to monitor and react to long-term processes like pollution spread, humidity levels, and seasonal migration of animal groups, as well as randomly occurring real-time events like pollution outbreaks, forest fires, and sightings of rare animals. To this end, the research team will abstract different capacities of plants—their distributed movements from slow to ballistic speed, adaptation according to ambient conditions, and energy harvesting processes—to establish new approaches toward robotic structure, motion, and functionality. On the education and outreach front, the award will support curriculum development in bio-inspired robotics, participation of undergraduate students in research, and outreach activities for middle school girls.The objective of this research is to enable development of plant-inspired robots capable of long-duration service in complex, dynamic environments by pursuing significant innovations in structural, energetic, and operational designs of robots, e.g., robotic hardware that mimics plant-like “growth” and adaptation; advancement in robotic movements to cover both real-time events (seconds/minutes) and long-term processes (weeks/months); and energy harvesting components for long-duration autonomy. The research team will achieve the objective by: (1) leveraging origami principles to create robotic “trunk” components capable of discrete and energy efficient growth-like deformations via folding and self-locking; (2) using principles from continuum robots to devise “leaf” and “needle” components capable of continuous and short-duration motions for monitoring and manipulating the ambient environment; (3) laying down the foundation for energy autonomy by exploring diverse energy harvesting approaches similar to those that plants employ; and (4) integration to enable multiple time-scale operations. Finally, this new concept of plant-inspired growing robots will be validated and evaluated via fully functional prototypes applied to campus pedestrian traffic and natural habitat monitoring in long-duration outdoor demonstrations.This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).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.

该奖项支持基础研究，以创建受植物启发的机器人，用于在充血和动态发展的环境中长期监测任务。这些环境在我们世界中比比皆是，例如，城市购物区，热带森林，水下礁石和未开发的岛屿。这些位置通常是无法访问的，并且用于人类运营的资源限制，并且随着时间的流逝，它们的发展缓慢但大大进化（例如，传播植被）。然而，在这些环境中“就在那里”并在多个时间范围内对事件做出反应至关重要，尤其是对于环境保护。因此，在这个项目中，将旨在监视和反应长期的过程，例如污染蔓延，湿度蔓延，动物群体的季节性迁移以及动物群体的季节性迁移，以及随机发生的实时事件，例如污染的动物，这些动物爆发了这些爆发，这些动物遇到了这些爆发，这些动物遇到了这些灾难，这些动物和森林爆发了这些，这些动物和这些动物的范围是这些，这些动物和森林爆发了这些，这些疾病和较少的动物是造成的。植物 - 它们从缓慢到弹道速度，根据环境条件进行适应以及能量收获过程的分布，以建立用于机器人结构，运动和功能的新方法。通过在机器人的结构，能源和运营设计中进行重大创新，例如，例如模仿植物般的“生长”和适应的机器人硬件，在复杂，动态的环境中进行长期服务；机器人运动的进步涵盖了实时事件（秒/分钟）和长期过程（周/月）；以及用于长期自治的能源收集组件。研究团队将通过以下方式实现目标：（1）利用折纸原则来创建能够通过折叠和自我锁定的机器人“躯干”组件，具有离散和节能的生长变形； （2）使用持续机器人的原理来设计“叶子”和“针头”组件，能够连续和短期运动，以监视和操纵环境环境； （3）通过探索潜水员的能源收集方法与工厂雇员类似，为能源自治奠定了基础； （4）集成以实现多个时间尺度操作。最后，将通过适用于校园行人交通和自然栖息地监视的全面功能原型来验证和评估这个新的植物启发机器人的新概念。法定使命，并通过评估诚实地认为，使用基金会的智力优点和更广泛的影响审查标准。