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: 2312423
• 负责人: Ian Walker
• 金额: $ 33.93万
• 依托单位: Clemson 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=2312423&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，以创建植物启发的机器人，用于在拥挤和动态变化的环境中执行长期监测任务。这样的环境在我们的世界中比比皆是，例如，城市购物区，热带森林，水下珊瑚礁和未开发的岛屿。这些位置对于人类操作来说通常是不可访问的并且资源有限，并且它们随着时间的推移缓慢但实质性地演变（例如，繁殖植物）。然而，在这些环境中“就在那里”并在多个时间尺度上对事件作出反应是至关重要的，特别是对于环境保护来说。因此，在这个项目中，植物启发的机器人将被设计用于监测和应对长期过程，如污染扩散，湿度水平和动物群体的季节性迁移，以及随机发生的实时事件，如污染爆发，森林火灾和稀有动物的目击。为此，研究团队将抽象植物的不同能力--它们从慢速到弹道速度的分布式运动、根据环境条件的适应以及能量收集过程--以建立机器人结构、运动和功能的新方法。在教育和推广方面，该奖项将支持生物启发机器人的课程开发，本科生参与研究，以及中学女生的推广活动。该研究的目标是通过在机器人的结构，能量和操作设计方面进行重大创新，开发能够在复杂，动态环境中长期服务的植物启发机器人，例如，机器人硬件模仿植物般的“生长”和适应;机器人运动的进步，以涵盖实时事件（秒/分钟）和长期过程（周/月）;以及用于长期自主的能量收集组件。研究小组将透过以下方法达致目标：（1）利用折纸原理，创造机器人“躯干”组件，透过折叠和自锁，使其能以不连续和具能源效益的方式变形;（2）利用连续体机器人的原理，设计“叶子”和“针”组件，使其能以持续和短时间的方式运动，以监测和操控周围环境;（3）通过探索与工厂采用的方法类似的多种能量收集方法，为能源自主奠定基础;以及（4）集成以实现多个时间尺度的操作。最后，这种植物启发的生长机器人的新概念将通过全功能原型进行验证和评估，这些原型将应用于校园行人交通和自然栖息地监测，并在长时间的户外演示中进行。该项目得到跨部门机器人基础研究计划的支持，由工程局（ENG）和计算机与信息科学与工程局（CISE）共同管理和资助该奖项反映了NSF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。