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Collaborative Research: Design, Flight Control, and Autonomous Navigation of Bioinspired Morphing Micro Aerial Vehicles for Operation in Confined Spaces

Collaborative Research: Design, Flight Control, and Autonomous Navigation of Bioinspired Morphing Micro Aerial Vehicles for Operation in Confined Spaces
合作研究:用于密闭空间操作的仿生变形微型飞行器的设计、飞行控制和自主导航
批准号:
2142519
负责人:
Alireza Ramezani
金额:
$65.23万
依托单位:
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
项目状态:
未结题
起止时间:
2022-05-15 至 2025-04-30

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中文摘要
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英文摘要
This project will promote the progress of science in aerial robotics and advance the national prosperity and welfare, by creating bat-inspired drones that can operate in extremely confined spaces. There is an increased demand for fast, continuous environmental surveillance in city sewers. These confined spaces occupy a large portion of a city's infrastructure. However, today's conventional robots, including ground and aerial systems, cannot operate in a vast majority of sewers. Sewer networks present a veritable maze of pipes, chambers, and utility holes that pose tremendous challenges for robot locomotion control and navigation. Therefore, human operators still inspect these dangerous spaces. In addition to carrying many risks for humans, manned operations in these environments are costly and slow. This grant’s research will contribute to the design of aerial, bat-inspired robots that can operate in sewers, by mimicking bat aerial locomotion principles in caves. The results from this research will greatly benefit the society. Especially during a pandemic, the continuous and automated monitoring of a city’s aging sewer systems using these bat-inspired drones can play a vital role in saving human lives. For instance, SARS-CoVs can be present in wastewater for several days, and its early detection in sewers in 2019 could have allowed for increased preparedness in combating the current pandemic. This project trains new generation scientists, engineers, and technologists with interdisciplinary skills, providing future professionals with vertically integrated, use-inspired experiential learning activities.Today's rotary-wing drones are better solutions for inspection and monitoring city infrastructure than ground robots because they are scalable, inexpensive, easy to deploy, and possess fast mobility. However, these systems cannot fly inside tight areas such as tunnels with small cross-sections because they rely on powerful and continuous air jets. So far, the confined space applications of these drones include only flying inside buildings or very spacious confined environments, which are not comparable to the application of aerial robots in sewers. This research will allow drones to complete fully autonomous flights inside tight spaces such as sewer galleries. The research team will (i) use an integrated mechanical intelligence and control framework to design drones with dynamically versatile body conformations and significant computational complexity to prevent creation of powerful air jets, (ii) design an integrated model-based and data-driven flight control framework that captures not only the model uncertainty but also the environmental aerodynamic effects that arise due to flight in tunnels, and (iii) develop a novel navigation framework that relies on high-level abstract guidance extracted from sewer schematic diagrams, enabling robust navigation in unmapped environments.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.
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CAREER: Dynamic Locomotion with Plasticity for Remote Sensing in Crawlspaces
  • 批准号:
    2340278
  • 项目类别:
    Standard Grant
  • 资助金额:
    $68.12万
  • 财政年份:
    2024
  • 负责人:
    Alireza Ramezani
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
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