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SBIR Phase II: Micro-Fluidic LiDAR for Autonomous Vehicles

SBIR Phase II: Micro-Fluidic LiDAR for Autonomous Vehicles
SBIR 第二阶段:用于自动驾驶汽车的微流控激光雷达
批准号:
1853156
负责人:
Andrew Miner
金额:
$74.97万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-15 至 2023-03-31

项目摘要

项目成果

Andrew Miner的其他基金

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中文摘要
翻译
该项目更广泛的影响/商业潜力是加快自动交通系统的部署,这将减少驾驶事故和死亡人数,实现城市设计的新范式,减少车辆交通,提高汽车效率,改善空气质量,有利于驾驶员和非驾驶员的直接健康。降低人员和货物运输成本将增加几乎所有产品和服务的利润,因为几乎所有活动都需要某种形式的运输。高级驾驶员辅助系统(ADAS)是半自动控制系统的简单实现,但已经通过提供智能巡航控制、车道偏离警告、转向辅助和先发制人的紧急制动来挽救生命。随着ADAS通过先进的传感器和扫描硬件得到改进,并得到更广泛的部署,将避免更多的事故,挽救更多的生命。由于扫描系统的限制,目前还没有能够感应超过200米的LiDAR成像传感器,并且还没有经过汽车认证。这项创新将首次提高对限制大规模传感器部署的可靠性问题的科学和技术理解,并导致第一批汽车合格的远程LiDAR传感器。这项小型企业创新研究(SBIR)第二阶段项目将产生一个汽车级激光扫描系统,使下一代LiDAR,一种三维成像传感器,对于自动送货机器人、无人机、车辆中的高级驾驶员安全系统和自动驾驶车辆的广泛采用至关重要。调查级激光雷达是一项成熟的技术,但由于更苛刻的冲击和振动要求,使其具有道路价值的努力失败了,部署的系统在两年内失败,并在高冲击条件下显示图像失真。拟议的创新将通过开发利用浮力抵消外部加速度的流体稳定光机械扫描仪来实现第一个汽车合格的远程LiDAR传感器。新的扫描仪技术将模拟,制造,并根据ISO规范进行测试,以证明准确的真实的时间扫描仪稳定性和长期可靠的操作。预计结果将是扫描仪能够通过ISO测试的形式兼容大批量,低成本的生产方法。通过与客户的合作,这项工作将产生一种新的视觉系统,将运输的效率和安全性提高到一个新的水平。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。
英文摘要
The broader impact/commercial potential of this project is to hasten the deployment of autonomous transportation systems, which stand to reduce driving accidents and fatalities, enable new paradigms in urban design, reduce vehicle traffic, increase automobile efficiency, and improve air quality, benefiting the immediate health of drivers and non-drivers alike. A reduction in cost of transporting people and goods would increase the profitability of nearly all products and services, since nearly all activities require transportation in some form. Advanced Driver Assistance Systems (ADAS) are simpler implementations of semi-autonomous controls systems but are already saving lives by providing intelligent cruise control, lane departure warnings, steering assistance, and preemptive emergency braking. As ADAS improves through advanced sensor and scanning hardware and becomes more widely deployed, more accidents will be avoided, and lives saved. There are currently no LiDAR imaging sensors that can sense greater than 200 meters and are automotive qualified due to limitations on the scanning systems. The proposed innovation would be the first to enhance a scientific and technical understanding of the reliability issues limiting wide-scale sensor deployment and result in the first automotive qualified long-range LiDAR sensors.This Small Business Innovation Research (SBIR) Phase II project will result in an automotive-grade laser scanning system that enables next generation LiDAR, a three- dimensional imaging sensor crucial for the widespread adoption of autonomous delivery robots, drones, advanced driver safety systems in vehicles, and autonomous vehicles. Survey-grade LiDAR is a mature technology, but efforts to make it road worthy have failed due to the harsher shock and vibration requirements and deployed systems fail within two years and display image distortion under high-shock conditions. The proposed innovation will result in the first automotive qualified long-range LiDAR sensor by developing fluid stabilized opto-mechanical scanners that utilize buoyant forces to counteract external accelerations. The novel scanner technology will be simulated, fabricated, and tested against ISO specifications for automotive qualification to demonstrate both accurate real time scanner stability and long-term reliable operation. It is expected that the results will be scanners able to pass ISO testing in a form compatible with high-volume, low-cost production methods. Through collaboration with customers, this work will result in a new class of vision systems that will bring a new level of efficiency and safety in transportation.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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会议论文
SHF: Medium: Improving the Efficiency and Applicability of Decision Diagrams
  • 批准号:
    2212142
  • 项目类别:
    Standard Grant
  • 资助金额:
    $70.0万
  • 财政年份:
    2022
  • 负责人:
    Andrew Miner
  • 依托单位:
SBIR Phase I: Micro-Fluidic LiDAR for Autonomous Vehicles
  • 批准号:
    1747116
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
    2018
  • 负责人:
    Andrew Miner
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SI2 - SSE: A Next-Generation Decision Diagram Library
  • 批准号:
    1642397
  • 项目类别:
    Standard Grant
  • 资助金额:
    $49.87万
  • 财政年份:
    2017
  • 负责人:
    Andrew Miner
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Midwest Verification Day 2016
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    1707092
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.0万
  • 财政年份:
    2016
  • 负责人:
    Andrew Miner
  • 依托单位:
国内基金
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地幔含水相Phase E的温度压力稳定区域与晶体结构研究
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基于数字增强干涉的Phase-OTDR高灵敏度定量测量技术研究