I-Corps: On-line image analysis and dynamic mission planning for unmanned aerial vehicles

I-Corps：无人机的在线图像分析和动态任务规划

• 批准号: 1720695
• 负责人: Girish Chowdhary
• 金额: $ 5万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1720695&HistoricalAwards=false
• 关键词: Corps; line; image; analysis; dynamic

This I-Corps project explores the commercial applicability of novel image analysis and feature detection algorithms and dynamic path planning algorithms. The broader impact/commercial potential of this I-Corps project include creation and commercialization of a software product for monitoring agricultural and natural landscapes using unmanned aerial systems. The benefits of commercialization of this advanced technology are expected to include improvement in the profitability and productivity of major food crops, increase in food security, and enable long-term sustainability of the nation's agronomic and natural resources. The proposed customer-interaction efforts will also lead to increased technical capacity among stakeholders in US agriculture and natural resource management sectors as they will involve intensive interaction between the proposing team with scientific and technical expertise, and the stakeholders in the target customer segments who have the necessary on-the-ground experience.This I-Corps project's image analysis and feature detection algorithms and dynamic path planning algorithms have been developed for rapid and computationally efficient detection of anomalous areas in visual spectrum images using mobile processors. The dynamic path planning algorithms enable automatic mid-flight modification of drone flight plans based on analysis of incoming data from drone-based sensors. Together these algorithms enable autonomous capture of high-value information and immediate delivery of actionable insights from drone missions. This technology will be a significant improvement on existing commercial offerings for drone-based monitoring, which involve high labor and equipment costs, require cloud-connectivity for data analysis, and are difficult to use and understand. By contrast, the fundamentally new workflow paradigms and innovative technical advances that will be examined here will enable rapid delivery of actionable insights about potential problems in remote environments using consumer level drones and visual spectrum cameras.

这个I-Corps项目探索了新的图像分析和特征检测算法以及动态路径规划算法的商业适用性。这个I-Corps项目的更广泛的影响/商业潜力包括使用无人机系统监测农业和自然景观的软件产品的创建和商业化。这种先进技术商业化的好处包括提高主要粮食作物的盈利能力和生产力，增加粮食安全，并使国家的农艺和自然资源能够长期可持续发展。拟议的客户互动工作还将提高美国农业和自然资源管理部门利益相关者的技术能力，因为它们将涉及具有科学和技术专业知识的提议团队与具有必要实地经验的目标客户群利益相关者之间的密切互动。这个I-Corps项目的图像分析和特征检测算法以及动态路径规划算法已经开发出来，用于使用移动处理器快速和计算高效地检测视觉光谱图像中的异常区域。动态路径规划算法能够基于对无人机传感器输入数据的分析，在飞行中途自动修改无人机的飞行计划。这些算法可以自动捕获高价值信息，并从无人机任务中立即提供可操作的见解。这项技术将是现有无人机监控商业产品的重大改进，后者涉及高劳动力和设备成本，需要云连接进行数据分析，并且难以使用和理解。相比之下，全新的工作流程范例和创新的技术进步将在这里进行研究，这将使使用消费级无人机和可视光谱相机在远程环境中快速提供有关潜在问题的可操作见解。