Collaborative Research: CPS: Medium: Wildland Fire Observation, Management, and Evacuation using Intelligent Collaborative Flying and Ground Systems

野火造成的损失日益增加，反映了气候变化和荒地的发展，这促使人们呼吁建立新的国家能力来管理野火。由于缺乏整体的、有弹性的、灵活的和具有成本效益的监测协议，无人机系统（UAS）的巨大潜力尚未在这一领域得到充分利用。该项目将开发基于无人机的火灾管理策略，以最佳、高效和安全的方式使用自主无人机（uav），在火灾探测、管理和疏散阶段协助第一响应者。该项目是北亚利桑那大学（NAU）、佐治亚理工学院（GaTech）、沙漠研究所（DRI）和国家大气研究中心（NCAR）的合作成果。该小组与美国林务局（USFS）在太平洋西北研究站、凯巴布国家森林（NF）和亚利桑那州林业和消防管理部建立了持续的合作关系，在规定和管理的火灾期间进行了多次实地测试。该提案的目标是开发一个综合框架，满足未满足的野火管理需求，通过在火灾管理操作的不同阶段使用低成本和小型自主无人机网络以及地面车辆，在科学和工程方法方面取得关键进展，包括：(i)使用自主无人机在偏远和森林地区进行早期检测；（ii）在无人机上对火灾热图进行快速主动地理制图；（iii）火灾蔓延的实时视频流；（iv）利用自主无人机寻找最佳疏散路径，引导地面车辆和消防员进行快速安全疏散。该项目将通过开发：(i)一种创新的基于无人机的森林火灾探测和监测技术，以最小的人为干预在难以进入的地区进行快速干预，以保护消防员的生命；（ii）多层次火力建模，提供战略、事件规模和新的机载低计算战术，使用无人机的快速火力映射；（iii）基于有限推理的规划机制，其中无人机在高度动态和不确定的危险区域为消防员和消防车确定最快和最安全的疏散道路。发达的技术将被转化为广泛的应用，例如灾害（洪水、火灾、泥石流、恐怖主义）管理，在这些应用中，需要在有限的人为干预下进行快速搜索、监视和响应。该项目还将有助于未来的工程课程，追求研究和教育的实质性整合，同时也吸引女性和代表性不足的少数民族学生，为K-12学生开发动手研究实验。该项目响应NSF网络物理系统20-563招标。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。

Increasing wildfire costs---a reflection of climate variability and development within wildlands---drive calls for new national capabilities to manage wildfires. The great potential of unmanned aerial systems (UAS) has not yet been fully utilized in this domain due to the lack of holistic, resilient, flexible, and cost-effective monitoring protocols. This project will develop UAS-based fire management strategies to use autonomous unmanned aerial vehicles (UAVs) in an optimal, efficient, and safe way to assist the first responders during the fire detection, management, and evacuation stages. The project is a collaborative effort between Northern Arizona University (NAU), Georgia Institute of Technology (GaTech), Desert Research Institute (DRI), and the National Center for Atmospheric Research (NCAR). The team has established ongoing collaborations with the U.S. Forest Service (USFS) in Pacific Northwest Research Station, Kaibab National Forest (NF), and Arizona Department of Forestry and Fire Management to perform multiple field tests during the prescribed and managed fires. This proposal's objective is to develop an integrated framework satisfying unmet wildland fire management needs, with key advances in scientific and engineering methods by using a network of low-cost and small autonomous UAVs along with ground vehicles during different stages of fire management operations including: (i) early detection in remote and forest areas using autonomous UAVs; (ii) fast active geo-mapping of the fire heat map on flying drones; (iii) real-time video streaming of the fire spread; and (iv) finding optimal evacuation paths using autonomous UAVs to guide the ground vehicles and firefighters for fast and safe evacuation. This project will advance the frontier of disaster management by developing: (i) an innovative drone-based forest fire detection and monitoring technology for rapid intervention in hard-to-access areas with minimal human intervention to protect firefighter lives; (ii) multi-level fire modeling to offer strategic, event-scale, and new on-board, low-computation tactics using fast fire mapping from UAVs; and (iii) a bounded reasoning-based planning mechanism where the UAVs identify the fastest and safest evacuation roads for firefighters and fire-trucks in highly dynamic and uncertain dangerous zones. The developed technologies will be translational to a broad range of applications such as disaster (flooding, fire, mud slides, terrorism) management, where quick search, surveillance, and responses are required with limited human interventions. This project will also contribute to future engineering curricula and pursue a substantial integration of research and education while also engaging female and underrepresented minority students, developing hands-on research experiments for K-12 students. This project is in response to the NSF Cyber-Physical Systems 20-563 solicitation.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.