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.

这项小型企业创新研究（SBIR）第二阶段项目的更广泛的影响 /商业潜力是，可以在房地产，农业，建筑，能源，娱乐，石油和新闻和新闻业等行业中更广泛地采用无人驾驶汽车（UAV）。 该项目开发具有无缝360度成像功能的高级无人机摄像头系统，以增加飞行时间和成像功能。最终用户受益于减少的人工需求和偏远地区的实时高保真图像，否则无法访问。工业检查，作物管理，现场测量和现场安全通常是通过将人部署到现场来进行的 - 经常会造成劳动瓶颈和潜在的危险情况。对于这些应用程序的采用，可以通过图像处理来限制无人机使用的图像处理，延迟的图像呈现影响导航功能，或者掩盖与市场需求相关的细节的图像伪像。 这些限制都可以通过此处开发的相机技术来克服。本小型企业创新研究（SBIR）II期项目开发了一种轻巧的，无差异的360度全景相机系统，其创新的光学设计基于相邻摄像机的多面体形状。每个摄像机的视野紧密相连，但并未与下一个视野重叠，从而可以从360度视图中对图像的无缝和计算简单捕获，同时限制了盲区和摄像机之间的内容丢失。这种方法消除了与广角镜头和多相机系统相关的缝线错误和图像失真，并减少了360度图像捕获的计算需求。结果，低能边缘计算机实时呈现图像，对无人机（无人机）应用中的飞行时间或能源使用的影响很小。此外，该项目推进了针对无人机的重量和尺寸进行优化的系统设计，并改进了运动学空间框架的概念，在该设计中，可以集成相机以形成强大的多相机系统。该奖项反映了NSF的法定任务，并通过该基金会的知识优点和广泛的creteria审查了NSF的法定任务。