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SBIR Phase I: TerraSentia: Ultra-compact, Autonomous, Teachable Under-canopy Phenotyping Robot for Plant Breeders and Crop Scientists

SBIR Phase I: TerraSentia: Ultra-compact, Autonomous, Teachable Under-canopy Phenotyping Robot for Plant Breeders and Crop Scientists
SBIR 第一阶段:TerraSentia:面向植物育种者和作物科学家的超紧凑、自主、可教学的树冠下表型机器人
批准号:
1820332
负责人:
Chinmay Soman
金额:
$22.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-07-01 至 2019-06-30

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中文摘要
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英文摘要
Broader Impacts: The broader impact of this Small Business Innovation Research (SBIR) project include improving food security, while at the same time enhancing the economic viability and environmental sustainability of large-scale production agriculture. In order to improve crop varieties, agricultural production, and sustainability of farming, there is an urgent need for better technologies to acquire under-canopy plant trait and health data. Examples of high-value under-canopy data include emergence, stem width, corn ear height, plant life-cycle events like flowering and fruiting, and symptoms of pathogens, diseases, and nutrient deficiency. Because these data cannot be obtained by aerial imaging, under-canopy data collection has dramatically greater actionability and value compared to aerial data. However no cost-effective, scalable ways of collecting this data are currently available. In fact, the state of the art is manual data collection by crop scientists (and their students or interns), agronomists, crop-scouts or farmers - an extremely labor intensive, and therefore expensive way of collecting this highly valuable data. Our work will greatly enhance the availability of under-canopy data from field crops. The commercial value of the field data for crop breeding is in excess of $50 Million/year for breeding major row-crops in the US.Intellectual Merits: This SBIR Phase I project will demonstrate the technical feasibility of autonomously collecting under-canopy data from field crops using TerraSentia, our low-cost ground robot. In preliminary work, we have built the robot hardware, demonstrated its ability to collect high-value plant data from row-crop fields, and analyze it to generate plant-trait information. In the proposed work, we will enable and demonstrate the ability of TerraSentia to collect data autonomously throughout the season. We will demonstrate the technical feasibility of fusing information from low-cost LIDAR, GPS, and vision. We will also demonstrate the feasibility using real-time control algorithms to adapt camera perspective and robot path in order to obtain the highest quality information from the complex and dynamic under- canopy field environments. These high-risk innovations will together enable long-term deployment of TerraSentia for effective data collection and phenotyping, benefiting crop scientists and agricultural product development professionals.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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STTR Phase II: TerraSentia: Ultra-compact, Autonomous, Teachable Under-canopy Phenotyping Robot for Plant Breeders and Crop Scientists
  • 批准号:
    1951250
  • 项目类别:
    Standard Grant
  • 资助金额:
    $75.0万
  • 财政年份:
    2020
  • 负责人:
    Chinmay Soman
  • 依托单位:
STTR Phase I: Autonomous Disinfecting Robot for Crowded Spaces
  • 批准号:
    2027693
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.6万
  • 财政年份:
    2020
  • 负责人:
    Chinmay Soman
  • 依托单位:
SEES Fellows: Soil Microbiomes and Agricultural Sustainability: An Integrated Metagenomic and Economic Investigation
国内基金
海外基金
Baryogenesis, Dark Matter and Nanohertz Gravitational Waves from a Dark Supercooled Phase Transition
  • 批准号:
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    省市级项目
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    --
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  • 批准号:
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  • 资助金额:
    3350万元
  • 批准年份:
    2019
  • 负责人:
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  • 依托单位:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
基于数字增强干涉的Phase-OTDR高灵敏度定量测量技术研究