Mechanical Intelligence of Locomotion and Intrusion in Slender Organisms in Terradynamically Rich Terrain

地动力丰富地形中细长生物体运动和入侵的机械智能

• 批准号: 2310751
• 负责人: Daniel Goldman
• 金额: $ 63万
• 依托单位: Georgia Tech Research Corporation
• 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: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2310751&HistoricalAwards=false
• 关键词: Mechanical; Intelligence; Locomotion; Intrusion; Slender

Most organisms navigate complex, heterogeneous, and unpredictable environments to survive. While the genes and cellular networks that regulate navigation, growth, and other exploratory behaviors differ, diverse living systems face common physical challenges. This suggests the possibility that at the organismal level, common control strategies (and hence general principles of movement) exist across living systems despite dramatic differences in the underlying biological mechanisms. In contrast to insights gained into movement in hydro and aerodynamics environments, principles by which organisms interact with complex, heterogeneous “terradynamically rich” environments are less understood. In such environments, organisms respond to ever-changing and unpredictable local interactions with limited sensory information; the strength of the interactions implies that the organism and its environment are highly coupled and cannot be regarded as independent systems. The centrality of the physical dynamics and incompleteness of environmental information suggests that terradynamically rich environmental locomotion requires both closed-loop, active sensory feedback (commonly associated with neural control in animals or decentralized chemical cues in plants) and open-loop, passively controlled, and purely physical processes. These latter processes, in which body-environment interactions are tuned to produce adaptive exploratory behaviors without the aid of active feedback control, constitute a mechanical intelligence. In this award the team of investigators seek to discover where, when, and how active closed-loop control and passive, mechanically intelligent control mechanisms interact to create goal-oriented organism movement in terradynamically rich environments. To do so they will use model systems that face similar challenges within their physical environments: 1) O. sativa (rice) and A. thaliana roots which must navigate complex soil environments; 2) C. elegans nematodes which undulate in soil and dense, rotting vegetative tissue; 3) limbless robots in dense, heterogeneous terrains, such as those encountered in agricultural areas and search and rescue operations. The investigators will study the kinematics, forces and genetics responsible for effective function. More broadly, their findings can give insight into the role of mechanics and control in evolution and organismal behavior, and at the same time, allow us to develop robots which can traverse natural environments with performance comparable to living systems. The studied biological and robotic systems are also natural subjects of popular interest and the scientific insights gained will be leveraged for educational and outreach purposes.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.

大多数生物体导航综合体，异质和不可预测的环境可以生存。尽管规范导航，增长和其他探索行为的基因和细胞网络不同，但潜水员生活系统面临着常见的身体挑战。这表明在有机水平上，尽管存在基本的生物学机制存在巨大差异，但在有机水平上，在生物系统中仍然存在共同的控制策略（因此，运动的一般原则）。与在水力学和空气动力学环境中获得运动的见解相反，有机体与复杂的，异质的“人性富裕”环境相互作用的原理较少了解。在这样的环境中，生物会对不断变化和不可预测的局部互动做出反应，并具有有限的感官信息。相互作用的强度意味着生物体及其环境是高度耦合的，不能被视为独立系统。物理动力学的中心性和环境信息的不完整性表明，众多的环境运动需要闭环，主动的感觉反馈（通常与动物的神经控制或植物中的分散化学提示相关）和开放环，并且被动控制和纯粹的物理过程。这些后来的过程（在无需主动反馈控制的情况下，都会调整身体环境相互作用以产生适应性的探索行为，这构成了机械智能。在该奖项中，调查人员团队试图发现在何时，何时以及如何在何时何地，机械智能控制机制相互作用，以创造面向目标的组织运动在Terradynysladymance上富裕的环境中。为此，他们将使用模型系统在其物理环境中面临类似挑战的模型系统：1）O。sativa（大米）和A. thaliana根部必须在复杂的土壤环境中驾驶； 2）秀丽隐杆线虫线虫在土壤和致密，腐烂的植物组织中散发； 3）在密集的，异质的地形中，例如在农业地区遇到的限制地形以及搜救行动。研究人员将研究负责有效功能的运动学，力和遗传学。更广泛地说，他们的发现可以深入了解力学和控制在进化和有机行为中的作用，同时允许我们开发机器人，这些机器人可以以与生活系统相当的性能穿越自然环境。研究生物的生物学和机器人系统也是自然感兴趣的自然主题，而获得的科学见解将用于教育和宣传目的。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准通过评估来获得支持的。