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BRITE Pivot: Towards Intelligent Health Monitoring, Inspection, and Reconnaissance of Critical Infrastructure using Autonomous Robots

BRITE 支点：利用自主机器人实现关键基础设施的智能健康监测、检查和侦察

基本信息

批准号：
2135732
负责人：
Gustavious Williams
金额：
$ 59.58万
依托单位：
Brigham Young University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135732&HistoricalAwards=false
关键词：
BRITE Pivot Towards Intelligent Health

项目摘要

This Boosting Research Ideas for Transformative and Equitable Advances in Engineering (BRITE) project will advance the ability of autonomous machines to inspect critical infrastructure with minimal human assistance through novel research in areas of machine learning, optimization, and computer vision. This objective will be achieved through a mentored and rigorous program comprised of classroom learning and focused research tasks intended to advance the ability for a small unmanned aerial vehicle (UAV or “drone”) to remotely and autonomously inspect a new, unknown, and cluttered infrastructure environment to find a potential threat using computer vision. By educating and training a group of civil engineering researchers in cutting-edge theory and methods of machine learning, optimization, and computer vision, this project will enable future research in a wide range of exciting and societally transformative topics related to autonomous infrastructure and smart cities. Without autonomous inspection, monitoring, and reconnaissance solutions, engineers are bottlenecked by humans in the loop. This research addresses the critical gap by exploring means for aerial robots to autonomously navigate in, model, and inspect cluttered urban environments. Computer vision, machine learning, and artificial intelligence will be used to improve reconnaissance of infrastructure before and after natural and/or man-made hazards. The potential for machines to autonomously and intelligently contribute to the safety and functionality of our society will not only improve the economics of monitoring society’s infrastructure, but it will also improve the quality of life for its residents by helping to maintain a more functional and safe society.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.

这个促进工程变革和公平进步的研究思路（BRITE）项目将通过机器学习，优化和计算机视觉领域的新研究，提高自主机器在最少的人力协助下检查关键基础设施的能力。这一目标将通过一个指导和严格的计划来实现，该计划包括课堂学习和重点研究任务，旨在提高小型无人机（UAV或“无人机”）远程和自主检查新的，未知的和杂乱的基础设施环境的能力，以使用计算机视觉找到潜在的威胁。通过对一批土木工程研究人员进行机器学习、优化和计算机视觉等前沿理论和方法的教育和培训，该项目将使未来的研究能够深入到与自主基础设施和智能相关的一系列令人兴奋且具有社会变革性的主题。城市。如果没有自主检查、监控和侦察解决方案，工程师将在循环中被人类检查。这项研究通过探索空中机器人在杂乱的城市环境中自主导航、建模和检查的方法来解决这一关键差距。计算机视觉、机器学习和人工智能将用于改善自然和/或人为灾害发生前后的基础设施侦察。机器自主和智能地为我们社会的安全和功能做出贡献的潜力不仅将改善监控社会基础设施的经济性，该奖项反映了国家科学基金会的法定使命，并通过利用基金会的智力价值进行评估，被认为值得支持和更广泛的影响审查标准。