Computer vision algorithms for aerospace applications

航空航天应用的计算机视觉算法

• 批准号: 298246-2007
• 负责人: Okouneva, Galina
• 金额: $ 1.17万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=366016
• 关键词: Computer; vision; algorithms; aerospace; applications

This proposal describes continuing research sponsored by NSERC held in the Computer Vision Management Laboratory (CVML) at the Department of Aerospace Engineering of Ryerson University. Dr. Okouneva's research interests lie in the area of applications of computer vision to the aerospace industry. In the space domain, applications include planetary exploration, on-orbit rendezvous and spacecraft inspection, automatic docking and satellite servicing operations. Dr. Okouneva's proposed research program research program includes the following projects: 1) Feature selection for 3D registration of range images of spacecraft objects. This project includes the research and development of an intelligent procedure of feature selection on spacecraft objects to achieve the best registration accuracy; 2) Research on properties of the initial guess for iterative pose estimation algorithms, in particular, what parameters of a pose estimation problem affect the initial guess and how to optimally choose it; 3) Optimal Strategy of Target Placement on Spacecraft Surfaces. The goal of this project is to estimate a possible accuracy improvement when targets form an optimized set on the surface of a spacecraft module.The research described in this proposal has substantial significance both for Canada and for the computer vision community as a whole. Future planetary exploration missions, development of satellite technology and satellite servicing, increasing safety requirements for spacecraft vehicles, and on-orbit astronaut's work require reliable vision systems. Dr. Okouneva research programs will highlight perspective avenues for innovation in space vision applicable to industry and academia. The proposed research contributes significantly to the training of highly qualified personnel. The program will support a PhD student and two MASc students each year. Students contributing to the proposed research will gain valuable skills and knowledge. Direct exposure to modern Computer Vision techniques will aid them in developing technical expertise, special engineering knowledge and expertise in computer science which are required for engineering leadership.

该提案描述了由NSERC在瑞尔森大学航空航天工程系计算机视觉管理实验室（CVML）赞助的持续研究。Okouneva博士的研究兴趣在于计算机视觉在航空航天工业中的应用。在空间领域，应用包括行星探索、在轨会合和航天器检查、自动对接和卫星服务操作。Okouneva博士提出的研究计划研究计划包括以下项目：1）航天器物体距离图像三维配准的特征选择。该项目包括研究和开发航天器目标特征选择的智能过程，以达到最佳的配准精度; 2）研究迭代位姿估计算法的初始猜测的性质，特别是位姿估计问题的哪些参数影响初始猜测以及如何最佳地选择它; 3）航天器表面目标放置的最佳策略。这个项目的目标是估计可能的精度提高时，目标形成一个优化的表面上的航天器model.The研究中描述的建议有实质性的意义，加拿大和整个计算机视觉界。未来的行星探索任务、卫星技术和卫星服务的发展、航天器安全要求的提高以及宇航员的在轨工作都需要可靠的视觉系统。Okouneva博士的研究计划将突出适用于工业和学术界的空间视觉创新的前景。该研究对培养高素质人才具有重要意义。该计划每年将支持一名博士生和两名MASc学生。为拟议研究做出贡献的学生将获得宝贵的技能和知识。直接接触现代计算机视觉技术将有助于他们发展工程领导所需的技术专长，特殊工程知识和计算机科学专业知识。