Autonomous and high-precision mapping via vision-guided unmanned aerial systems

通过视觉引导无人机系统进行自主高精度测绘

• 批准号: RGPIN-2017-03881
• 负责人: Shahbazi, Mozhdeh
• 金额: $ 1.6万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=678601
• 关键词: Autonomous; precision; mapping; via; vision

In recent years, integrating three-dimensional (3D) vision to unmanned aerial vehicles (UAVs) has contributed a great deal to the advancement of geo-spatial technologies for fine-scale mapping. Despite the recent efforts, exploiting these systems to their maximum potential has remained limited due to the lack of extensive research and development with respect to the following aspects: increasing the precision, safety and intelligence of navigation; improving the quality and autonomy of data acquisition; integrating multiple complementary data-collection technologies; enhancing techniques of data processing to raise the level of accuracy, completeness, and interpretability of the outputs. In this regard, the long-term objective of my research program (10+ years) is to develop novel approaches for emerging cognitive and collaborative 3D-vision solutions in geomatics engineering. The geomatics applications of these solutions include the broad areas of infrastructure inspection, law enforcement, search and rescue, on-demand emergency mapping, city modeling, wildlife management, and precision farming. ***To meet my long-term research goals, this short-term research program will address the challenges related to the development of intelligent stereo-vision systems based on unmanned aerial vehicles. Particularly, the thematic application of the proposed solutions will be high-precision surveying and metric inspection of urban infrastructure. Examples of such structures are vertically extended ones (e.g. telecommunication towers and building facades) and linearly extended ones (e.g. power lines and roads). The specific objectives of this research program include the following: 1) Developing vision-based techniques of precise pose estimation and navigation, 2) Task-based active view planning for autonomous image acquisition, and 3) Semantic stereo-vision computation for automated and accurate 3D mapping of infrastructure.***The outcomes of the proposed research have the potential to significantly advance and revolutionize the techniques of infrastructure mapping and inspection. The systems and approaches developed in this research program will result in the autonomous production of high-accuracy 3D measurements and collection of detailed visual data from infrastructure. The solutions can easily compete with the current human-centric methods of observation and will eliminate the need to put lives of inspectors at risk to manually inspect hard-to-reach assets. In addition to infrastructure industries, the achievements of this research program are transferable to other domains of engineering wherever there is a need for high-precision autonomous mapping. The HQP trained in this program will be able to transfer their knowledge and skills to Canadian industries in the vast fields of applications for mapping and monitoring via modern geo-spatial technologies.

近年来，将三维（3D）视觉集成到无人机（UAV）上，极大地促进了地理空间技术的进步，以实现精细比例尺制图。尽管最近作出了努力，但由于在以下方面缺乏广泛的研究和开发，最大限度地利用这些系统的潜力仍然有限：提高导航的精确度、安全性和智能性;提高数据采集的质量和自主性;整合多种互补的数据收集技术;加强数据处理技术，以提高产出的准确性、完整性和可解释性。在这方面，我的研究计划（10年以上）的长期目标是为地理信息工程中新兴的认知和协作3D视觉解决方案开发新方法。这些解决方案的地理信息应用包括基础设施检查、执法、搜索和救援、按需应急测绘、城市建模、野生动物管理和精准农业等广泛领域。*** 为了实现我的长期研究目标，这个短期研究计划将解决与基于无人机的智能立体视觉系统开发相关的挑战。特别是，拟议解决方案的专题应用将是城市基础设施的高精度测量和计量检查。这种结构的例子是垂直延伸的结构（例如电信塔和建筑物立面）和线性延伸的结构（例如电力线和道路）。该研究计划的具体目标包括：1）开发基于视觉的精确位姿估计和导航技术，2）基于任务的主动视图规划，用于自主图像采集，以及3）语义立体视觉计算，用于自动化和精确的基础设施3D映射。拟议研究的成果有可能大大推进和革新基础设施测绘和检查技术。该研究计划开发的系统和方法将导致高精度3D测量的自主生产和从基础设施收集详细的视觉数据。这些解决方案可以很容易地与目前以人为中心的观察方法竞争，并将消除将检查员的生命置于危险之中以手动检查难以到达的资产的必要性。除了基础设施行业外，该研究计划的成果还可以转移到其他需要高精度自主测绘的工程领域。在该计划中接受培训的HQP将能够通过现代地理空间技术将其知识和技能转移到加拿大工业的测绘和监测应用的广泛领域。