Photometry and radiometry-based metrology for design and development of high-precision fully-autonomous robotic inspection systems

基于光度测量和辐射测量的计量,用于设计和开发高精度全自动机器人检测系统

基本信息

  • 批准号:
    RGPIN-2017-06294
  • 负责人:
  • 金额:
    $ 1.82万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2018
  • 资助国家:
    加拿大
  • 起止时间:
    2018-01-01 至 2019-12-31
  • 项目状态:
    已结题

项目摘要

The long-term objective of my research is to focus on developing methods to optimally integrate high-precision multi-spectral imaging sensors with the operation of unmanned systems to create high precision products, inspection tools, and manufacturing processes. In particular, photometry- and radiometry-based metrology for unmanned systems have been drawing a significant attention within the research community since they surpass other sensors known to the man kind in terms of information transfer capacity and the required acquisition/processing time. The missing piece in this puzzle, aside from physical challenges at the manufacturing level, however, is the lack of intelligent, yet robust information filters to deal with the massive data generated by wide-spectrum imaging sensors. ***The research community is pushing resolutely on developing industry standards for: (1) generating Point Clouds from hyper-spectral images obtained via imaging sensors at different vantage pints, (2) organizing the Point Cloud based on the motion information obtained via the unmanned systems carrying them, and (3) stitching the overlapping Point Clouds together to generate a 3D Structure From Motion (SFM). While there has been some significant work in this area around the visible-light imaging systems, very little has been done on imaging systems beyond visible spectrum. ***My long-term research plan is to focus and contribute in this area: Design and development of algorithmic procedures for precise metrology when using imaging sensors onboard unmanned mobile systems with a wide spectral range beyond visible light. ***The applicant and his team will focus on two programs during the project's life cycle as follows: ******Program one: Development of photometry- and radiometry-based metrology techniques with applications in inspecting infrastructure, industrial processes, and manufacturing.***Program two: Photometry- and Radiometry-based metrology for automated and precision agriculture. ******In program one, the main focus will be 3D reconstruction through Structure From Motion using imaging sensors within an electromagnetic spectrum beyond that in visible light. In particular, the 3D reconstruction of the thermal footprint of an object using thermal cameras will be investigated.******In program two, my research plan is to focus on three areas of the automated and precision agronomy as: (1) automated seeding and fertilization, (2) automated weed detection and removal, and (3) autonomous collaborative harvesting. I will focus on algorithmic development of the photometry- and radiometry-based metrology in precision agriculture. I own a 25-hp tractor that was turned to a fully autonomous system in my research lab. Students recruited for this program will have access to this unique automated tractor. To the best of my knowledge, no other research lab provides an experimental setup with this caliber.
我研究的长期目标是专注于开发方法,将高精度多光谱成像传感器与无人系统的操作进行最佳集成,以创建高精度产品、检测工具和制造工艺。特别是,测光和辐射测量为基础的计量无人驾驶系统一直在研究界引起了极大的关注,因为它们超过了人类已知的其他传感器的信息传输能力和所需的采集/处理时间。然而,除了制造层面的物理挑战外,这个难题中缺少的部分是缺乏智能但强大的信息过滤器来处理宽光谱成像传感器生成的大量数据。* 研究界正在坚定地推动制定行业标准:(1)从通过成像传感器在不同Vantage位置获得的高光谱图像生成点云,(2)基于通过携带它们的无人系统获得的运动信息组织点云,以及(3)将重叠的点云拼接在一起以生成3D运动结构(SFM)。虽然在可见光成像系统的这一领域已经有了一些重要的工作,但在可见光谱以外的成像系统上做得很少。* 我的长期研究计划是专注于这一领域并做出贡献:设计和开发用于精确计量的算法程序,当使用无人驾驶移动的系统上的成像传感器时,其光谱范围超过可见光。 * 申请人及其团队将在项目生命周期内专注于以下两个项目:** 项目一:开发基于光度和辐射测量的计量技术,并应用于基础设施、工业流程和制造业的检测。计划二:自动化和精确农业的基于光度和辐射测量的计量。** 在第一个项目中,主要重点将是通过使用可见光以外的电磁频谱内的成像传感器,通过运动结构进行3D重建。特别是,将研究使用热成像仪对物体的热足迹进行3D重建。**在项目二中,我的研究计划重点关注自动化和精准农艺的三个领域:(1)自动化播种和施肥,(2)自动化杂草检测和清除,(3)自主协作收获。我将专注于精确农业中基于光度测量和辐射测量的计量学的算法开发。我拥有一台25马力的拖拉机,在我的研究实验室里变成了一个完全自主的系统。该计划招募的学生将有机会使用这种独特的自动化拖拉机。据我所知,没有其他研究实验室提供这种口径的实验装置。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Mehrandezh, Mehran其他文献

A Cascaded and Adaptive Visual Predictive Control Approach for Real-Time Dynamic Visual Servoing
  • DOI:
    10.3390/drones6050127
  • 发表时间:
    2022-05-01
  • 期刊:
  • 影响因子:
    4.8
  • 作者:
    Sajjadi, Sina;Mehrandezh, Mehran;Janabi-Sharifi, Farrokh
  • 通讯作者:
    Janabi-Sharifi, Farrokh
OPTIMAL SPATIAL RESOLUTION OF OMNIDIRECTIONAL IMAGING SYSTEMS FOR PIPE INSPECTION APPLICATIONS
  • DOI:
    10.1080/15599612.2015.1059536
  • 发表时间:
    2015-10-02
  • 期刊:
  • 影响因子:
    5.5
  • 作者:
    Tezerjani, Abbasali Dehghan;Mehrandezh, Mehran;Paranjape, Raman
  • 通讯作者:
    Paranjape, Raman

Mehrandezh, Mehran的其他文献

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{{ truncateString('Mehrandezh, Mehran', 18)}}的其他基金

Photometry and radiometry-based metrology for design and development of high-precision fully-autonomous robotic inspection systems
基于光度测量和辐射测量的计量,用于设计和开发高精度全自动机器人检测系统
  • 批准号:
    RGPIN-2017-06294
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Photometry and radiometry-based metrology for design and development of high-precision fully-autonomous robotic inspection systems
基于光度测量和辐射测量的计量,用于设计和开发高精度全自动机器人检测系统
  • 批准号:
    RGPIN-2017-06294
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Automated Assembly of Seeding Toolbars at Vaderstad
Vaderstad 播种工具栏的自动组装
  • 批准号:
    543925-2019
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Development Grants
Photometry and radiometry-based metrology for design and development of high-precision fully-autonomous robotic inspection systems
基于光度测量和辐射测量的计量,用于设计和开发高精度全自动机器人检测系统
  • 批准号:
    RGPIN-2017-06294
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Automated Assembly of Seeding Toolbars at Vaderstad
Vaderstad 播种工具栏的自动组装
  • 批准号:
    543925-2019
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Development Grants
Deep Convolutional Neural Networks for Identification, Tracking, and Classification of Transport Vehicles using Multiple-view Imaging Systems
使用多视图成像系统的深度卷积神经网络对运输车辆进行识别、跟踪和分类
  • 批准号:
    536767-2018
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Development Grants
Automated Assembly of Seeding Toolbars at Vaderstad
Vaderstad 播种工具栏的自动组装
  • 批准号:
    543925-2019
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Development Grants
Deep Convolutional Neural Networks for Identification, Tracking, and Classification of Transport Vehicles using Multiple-view Imaging Systems
使用多视图成像系统的深度卷积神经网络对运输车辆进行识别、跟踪和分类
  • 批准号:
    536767-2018
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Development Grants
Photometry and radiometry-based metrology for design and development of high-precision fully-autonomous robotic inspection systems
基于光度测量和辐射测量的计量,用于设计和开发高精度全自动机器人检测系统
  • 批准号:
    RGPIN-2017-06294
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Tempro-spatial measurement of wind speed/direction using rotary-wing UAVs
使用旋翼无人机进行风速/风向的时空测量
  • 批准号:
    531170-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Engage Grants Program

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Photometry and radiometry-based metrology for design and development of high-precision fully-autonomous robotic inspection systems
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基于光度测量和辐射测量的计量,用于设计和开发高精度全自动机器人检测系统
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