SBIR Phase II: Three Dimensional Monocular Thermal Ranging Camera

SBIR二期：三维单目热测距相机

• 批准号: 2128439
• 负责人: Eugene Petilli
• 金额: $ 99.83万
• 依托单位: OWL AUTONOMOUS IMAGING INC
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2128439&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Three; Dimensional

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve the safe operation of Advanced Driver-Assistance Systems (ADAS) equipped vehicles and robotic mobility machinery while helping overcome the sensing challenges that have delayed autonomous vehicle (AV) adoption and acceptance. Degraded Visual Environments (DVE) such as solar glare, darkness, smoke, and dust impact the safety of vehicle occupants, as well as those external to the vehicle, especially pedestrians and cyclists. The new sensor modality of the 3D monocular thermal technology developed as part of this project may improve the safe operation of on-road and off-road vehicles alike. The system seeks to detect and locate pedestrians, cyclists and objects in all conditions, improving vehicle automated braking, obstacle avoidance, localization, and navigation. Beyond improving safety, the new 3D monocular thermal modality devise will improve the utility and commercial value of vehicles and robotic machines by extending the operating range to include the most challenging environmental conditions.This Small Business Innovation Research (SBIR) Phase II project will develop a new sensor modality that addresses the shortcomings of camera, radar and LiDAR sensors used in current automotive and robotic mobility applications. This project seeks to develop the simple, yet powerful innovation of thermal monocular ranging where a single thermal camera produces 2D video detail concurrent with a range map or point cloud of much higher spatio-temporal density than contemporary sensors. Drawing inspiration from monocular convolutional neural network (CNN) ranging work recently published in the visible domain, this project creates a new field of monocular 3D thermal imaging. Unlike visible-based CNN systems that rely on color information and reflected light, this project will construct from first principles new thermal networks and ground truth sets to train the CNN. The extreme price pressures of the automotive market can only be met through adoption of a new thermal detector technology. This project further develops new thin-film detector technology and the detector to readout interconnect application process with potential breakthroughs in thermal camera performance, utility, and affordability.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.

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。这个小型企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力是改善配备高级驾驶辅助系统（ADAS）的车辆和机器人移动机械的安全操作，同时帮助克服延迟自动驾驶汽车（AV）采用和接受的传感挑战。太阳眩光、黑暗、烟雾和灰尘等退化的视觉环境（DVE）会影响车辆乘员以及车辆外部人员的安全，特别是行人和骑自行车的人。作为该项目的一部分，开发的3D单目热技术的新传感器模式可以提高公路和越野车辆的安全操作。 该系统旨在检测和定位各种条件下的行人、骑自行车的人和物体，改善车辆自动制动、避障、定位和导航。除了提高安全性，新的3D单目热模态设计将通过扩展操作范围来提高车辆和机器人机器的实用性和商业价值，包括最具挑战性的环境条件。这个小企业创新研究（SBIR）第二阶段项目将开发一种新的传感器模态，解决当前汽车和机器人移动应用中使用的摄像头，雷达和LiDAR传感器的缺点。该项目旨在开发简单但功能强大的热单目测距创新，其中单个热摄像机产生2D视频细节，同时具有比当代传感器高得多的时空密度的范围图或点云。从最近发表在可见光领域的单目卷积神经网络（CNN）测距工作中汲取灵感，该项目创建了一个新的单目3D热成像领域。与依赖于颜色信息和反射光的基于可见光的CNN系统不同，该项目将从第一原理构建新的热网络和地面真值集来训练CNN。汽车市场的极端价格压力只能通过采用新的热探测器技术来满足。该项目进一步开发了新的薄膜探测器技术和探测器读出互连应用过程，在热成像相机的性能，实用性和可负担性方面具有潜在的突破。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。