PFI-TT: Intelligent Flight Planning of Multiple Drones for Power Line Inspection

该创新技术转化伙伴关系（PFI-TT）项目的更广泛影响/商业潜力是实现多架无人机的自动化和同步检查。潜在客户包括电力公司、公共安全组织和无人机运营商。高效的基于无人机的电力线检查的好处包括提高线路人员的安全性，节省维护检查的成本（例如，检测电力线附近的植被），以及节省大量时间。在评估损坏并从风暴和飓风造成的中断中恢复时，利用多架无人机减少检查时间的能力至关重要。使用一组无人机的优点是可以同时检查多条电力线，从而使检查过程并行化，大大减少了人工操作员的任务时间。该团队将与无人机运营商和电力公司合作，进行概念验证配电线路检查，并评估该方法的有效性。该软件还可以应用于交通和能源行业，用于检查高速公路、铁路、石油和天然气管道。该项目团队将与该大学的技术商业化部门合作，并将发现更多潜在的合作伙伴。拟议的项目将为一组无人机开发、实施和验证飞行计划算法和软件，以有效地检查电力线。考虑到输配电线路的地理位置，以及无人机的数量和型号，无人机路由算法将自动为每架无人机从其所在地生成飞行计划。将解决的一个关键研究挑战是开发能够扩大规模以处理大面积密集电力线网络的有效算法。自动分配和协调多架无人机的能力，在电池限制，甚至可能是不同类型的情况下，以资源优化的方式，到电力线的不同部分，将是目前人工和无人机检查技术的重大进步。为了便于商业化使用，该软件将在云中运行，使现场工作人员能够从智能手机上获得自动生成的飞行计划。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to enable automated and simultaneous inspection by multiple drones. Potential customers include electric utility companies, public safety organizations, and drone operators. The benefits of efficient drone-based inspection of electric power lines include greater safety for linemen, cost savings for maintenance inspections (e.g., to detect vegetation near power lines), and substantial time savings. The ability to utilize multiple drones to reduce the inspection time can be critical when assessing damage and recovering from outages due to storms and hurricanes. The advantage of using a team of drones is that multiple power lines can be simultaneously inspected, thus parallelizing the inspection process and substantially reducing the mission time for the human operators. The team will partner with drone operators and electric utilities to perform a proof-of-concept distribution line inspection and to evaluate the effectiveness of the approach. There is also potential for applying the proposed software to the transportation and energy industries for inspection of highways, railroads, and oil and gas pipelines. The project team will work with the technology commercialization arm of the university and will discover additional potential partners.The proposed project will develop, implement, and validate flight planning algorithms and software for a team of drones to efficiently inspect power lines. Given the geographic locations of the power transmission and distribution lines, and the number and model of the drones, the drone routing algorithms will automatically generate flight plans for each of the drones from their home locations. A key research challenge that will be addressed is the development of efficient algorithms capable of scaling up to handle dense power line networks over large areas. The ability to automatically assign and coordinate multiple drones, with battery constraints and potentially even of different types, to different sections of the power lines in a resource-optimal manner will be a significant advance over the current state of the art in both manual and drone based inspection. To enable ease of use for commercialization, the software will run in the cloud, enabling workers in the field to obtain automatically generated flight plans from their smartphones.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.