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

该奖项支持基础研究，以创造以植物为灵感的机器人，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里比比皆是，例如，城市购物区、热带森林、水下暗礁和未开发的岛屿。这些地点通常无法进入，人工操作的资源有限，它们随着时间的推移而缓慢但实质上演变(例如，繁殖植被)。然而，在这些环境中“身临其境”并在多个时间尺度上对事件做出反应是至关重要的，特别是对环境保护而言。因此，在这个项目中，以植物为灵感的机器人将被设计成监测和应对长期过程，如污染传播、湿度水平和动物群体的季节性迁徙，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，研究小组将抽象植物的不同能力-它们的分布式运动从低速到弹道速度，根据环境条件进行适应，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，该奖项将支持仿生机器人的课程开发，本科生参与研究，以及针对中学女生的推广活动。这项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，例如，模仿植物般的“生长”和适应能力，促进以植物为灵感的机器人的开发，使其能够在复杂、动态的环境中长期服务；在机器人运动方面的进步，以涵盖实时事件(秒/分钟)和长期过程(周/月)；以及用于长时间自主的能量收集部件。研究小组将通过以下方式实现这一目标：(1)利用折纸原理创造能够通过折叠和自锁实现离散和高能效生长的机器人“树干”部件；(2)利用连续介质机器人的原理设计能够连续和短时间运动的“树叶”和“针”部件，用于监测和操纵周围环境；(3)通过探索与植物相似的不同能量收集方法，为能源自主性奠定基础；以及(4)集成，以实现多时间尺度操作。最后，这一植物启发成长机器人的新概念将通过应用于校园行人交通和自然栖息地长期户外演示的全功能原型进行验证和评估。该项目由跨部门机器人基础研究计划支持，该计划由工程总监(ENG)和计算机和信息科学与工程(CEISE)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智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.