EFRI BRAID: Resilient autonomous navigation inspired by the insect central complex and sensorimotor control motifs

EFRI BRAID：受昆虫中枢复合体和感觉运动控制图案启发的弹性自主导航

• 批准号: 2318081
• 负责人: Floris van Breugel
• 金额: $ 200万
• 依托单位: Board of Regents, NSHE, obo University of Nevada, Reno
• 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=2318081&HistoricalAwards=false
• 关键词: EFRI; BRAID; Resilient; autonomous; navigation

The last decade has seen a substantial increase in the frequency of natural disasters including wildfires, flooding, landslides, and outbreaks of agricultural pests and diseases. Mitigating the severity of disasters will require early warning and rapid responses, both of which could be aided by reliable and inexpensive autonomous robots. Unfortunately, modern robots have difficulty responding to new environments or damage to their bodies that might occur during disaster response. In contrast, living systems are remarkably adept at quickly adjusting their behavior to new situations thanks to redundancy and flexibility within the sensory and muscle control systems. Scientific discoveries in fruit flies have helped shed light on how these insects achieve resiliency in flight. The primary goal of this project is to translate this emerging knowledge from insect neuroscience to enable the development of more resilient robotic systems. This project builds on existing engineering theory to develop algorithms that are easy to understand and explain. As part of this project, unique research experiences will be offered to middle, high school, and undergraduate students to participate in both neuroscience and robotics research. The multidisciplinary research team will develop open-source course content to help bring neuroscience fluency to engineering students: translating neuroscience principles to engineering for enhanced resilience.A significant engineering challenge that has stymied the rollout of autonomous robotics is their lack of resilience in novel scenarios. In contrast, organisms are adept at quickly adjusting their behavior to new contexts thanks to redundancy and flexibility within their sensorimotor systems. Incorporating comparable functionality in engineered systems has proven challenging because we lack the basic knowledge for how to fuse information streams from different sensors and coordinate a large array of actuators without detailed models and constant calibrations—this sophisticated operation is achieved effortlessly by even simple animals. The overall goal of this proposal is to leverage recent neurobiological discoveries to develop new designs for autonomous robots that learn to adapt rapidly to changes in the environment or in their sensory and motor systems. The proposed approach draws inspiration from two themes found in insects: 1) the exploitation of a versatile, multisensory compass for navigation, and 2) the flexible implementation of stereotyped sensorimotor motifs in locomotion and other behaviors. The goals are to translate these concepts into engineering principles at an abstracted control-theoretic level, and then to implement and test them on functioning multirotor systems. This project is jointly funded by the Emerging Frontiers in Research and Innovation Program (BRAID) and the Established Program to Stimulate Competitive Research (EPSCoR).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.

在过去十年中，自然灾害的频率大幅增加，包括野火、洪水、山体滑坡以及农业病虫害的爆发。减轻灾害的严重程度需要早期预警和快速反应，这两者都可以得到可靠和廉价的自主机器人的帮助。不幸的是，现代机器人很难对新环境做出反应，或者在灾难应对过程中可能发生的身体损伤。相比之下，由于感觉和肌肉控制系统中的冗余和灵活性，生命系统非常善于快速调整其行为以适应新的情况。果蝇的科学发现有助于阐明这些昆虫如何在飞行中获得弹性。该项目的主要目标是将昆虫神经科学的新兴知识转化为能够开发更具弹性的机器人系统的知识。该项目建立在现有的工程理论基础上，开发易于理解和解释的算法。作为该项目的一部分，将为初中，高中和本科学生提供独特的研究经验，以参与神经科学和机器人研究。多学科研究团队将开发开源课程内容，以帮助工程专业的学生掌握神经科学的流利程度：将神经科学原理转化为工程学，以增强自主性。阻碍自主机器人推出的一个重大工程挑战是它们在新场景中缺乏弹性。相比之下，由于感觉运动系统的冗余性和灵活性，生物体善于迅速调整其行为以适应新的环境。在工程系统中实现类似的功能已经被证明是具有挑战性的，因为我们缺乏如何融合来自不同传感器的信息流的基本知识，并且在没有详细模型和不断校准的情况下协调大量执行器-即使是简单的动物也可以轻松实现这种复杂的操作。该提案的总体目标是利用最近的神经生物学发现来开发自主机器人的新设计，这些机器人学会快速适应环境或其感觉和运动系统的变化。所提出的方法从昆虫中发现的两个主题中汲取灵感：1）利用多功能，多感官的指南针进行导航，以及2）在运动和其他行为中灵活实施刻板的感觉运动基序。目标是将这些概念转化为抽象控制理论层面的工程原理，然后在多旋翼系统上实现和测试。该项目由新兴前沿研究与创新计划（BRAID）和激励竞争研究的既定计划（EPSCoR）共同资助。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。