SBIR Phase II: Fast Panoramic Image Capture for Unmanned Aerial Vehicles

SBIR 第二阶段：无人机快速全景图像捕获

• 批准号: 2136737
• 负责人: Andrew Kurtz
• 金额: $ 99.95万
• 依托单位: Circle Optics LLC
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2136737&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Fast; Panoramic

The broader impact / commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to enable wider adoption of unmanned aerial vehicles (UAVs) across industries such as real estate, agriculture, construction, energy, entertainment, oil & gas, and journalism. The project develops advanced UAV camera systems with seamless 360-degree imaging capabilities to increase flight time and the imaging capability. End users benefit from reduced labor demands and real-time high-fidelity images of remote areas otherwise inaccessible. Industrial inspections, crop management, field surveying, and site security are most often conducted by deploying humans into the field - often creating labor bottlenecks and potentially dangerous situations. Adoption of UAVs for these applications can be limited by image processing that consumes too much power for UAV use, delayed image presentation affecting navigation capabilities, or image artifacts that obscure the details pertinent to market needs. These limitations can all be overcome with the camera technologies developed here.This Small Business Innovation Research (SBIR) Phase II project develops a lightweight, parallax-free, 360-degree panoramic camera system with an innovative optical design based on a polyhedron-shaped configuration of adjacent cameras. Each camera's field of view closely abuts but does not overlap with the next, enabling seamless and computationally simplistic capture of images from 360-degree views, while limiting blind regions and lost content between cameras. This approach eliminates the stitching errors and image distortion associated with wide angle lenses and multi-camera systems, and reduces the computational demand for 360-degree image capture. As a result, low energy edge-computing presents images in real time with minimal impact on flight time or energy use in unmanned aerial vehicles (UAV) applications. Furthermore, this project advances system designs optimized for UAV weight and size, as well as improved concepts for kinematic space frames, in which the cameras can be integrated to form robust multi-camera systems.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.

该小企业创新研究 (SBIR) 第二阶段项目的更广泛影响/商业潜力是使无人机 (UAV) 在房地产、农业、建筑、能源、娱乐、石油和天然气以及新闻等行业得到更广泛的采用。 该项目开发具有无缝 360 度成像功能的先进无人机摄像系统，以增加飞行时间和成像能力。最终用户受益于劳动力需求的减少以及无法访问的偏远地区的实时高保真图像。工业检查、作物管理、现场测量和现场安全通常是通过将人员部署到现场进行的，这通常会造成劳动力瓶颈和潜在的危险情况。无人机在这些应用中的采用可能会受到以下因素的限制：图像处理消耗无人机使用过多的电量、影响导航功能的延迟图像呈现或模糊与市场需求相关的细节的图像伪影。 这些限制都可以通过这里开发的相机技术来克服。这个小型企业创新研究 (SBIR) 第二阶段项目开发了一种轻型、无视差、360 度全景相机系统，该系统采用基于相邻相机的多面体形状配置的创新光学设计。每个摄像头的视野紧密相邻但不重叠，从而能够从 360 度视图中无缝且计算简单地捕获图像，同时限制摄像头之间的盲区和内容丢失。这种方法消除了与广角镜头和多摄像头系统相关的拼接错误和图像失真，并减少了 360 度图像捕获的计算需求。因此，低能耗边缘计算可以实时呈现图像，对无人机 (UAV) 应用中的飞行时间或能源使用影响最小。此外，该项目还推进了针对无人机重量和尺寸进行优化的系统设计，以及改进的运动空间框架概念，其中摄像机可以集成以形成强大的多摄像机系统。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。