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

日益增加的野火成本-反映了气候变化和荒地内的发展-推动了对新的国家能力的要求，以管理野火。无人机系统（UAS）的巨大潜力尚未在这一领域得到充分利用，因为缺乏整体的，弹性的，灵活的，具有成本效益的监测协议。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），以协助火灾探测，管理和疏散阶段的第一响应者。该项目是北方亚利桑那大学（NAU）、格鲁吉亚理工学院（GaTech）、沙漠研究所（DRI）和国家大气研究中心（NCAR）之间的合作成果。该团队已与美国林务局（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，以便在规定和管理的火灾期间进行多次现场测试。该提案的目标是开发一个综合框架，满足未得到满足的荒地火灾管理需求，并在科学和工程方法方面取得关键进展，方法是在火灾管理行动的不同阶段使用低成本和小型自主无人机沿着地面车辆网络，包括：（i）使用自主无人机在偏远和森林地区进行早期探测;（ii）在飞行无人机上对火灾热图进行快速主动地理测绘;（iii）对火灾蔓延进行实时视频流传输;以及（iv）使用自主无人机寻找最佳疏散路径，以引导地面车辆和消防员快速安全疏散。该项目将通过开发以下技术推进灾害管理的前沿：㈠创新的无人驾驶飞机森林火灾探测和监测技术，用于在难以进入的地区进行快速干预，最大限度地减少人为干预，以保护消防员的生命; ㈡多级火灾建模，利用无人驾驶飞机的快速火灾测绘，提供战略性、事件规模和新的机载低计算战术;以及（iii）基于有界推理的规划机制，其中UAV在高度动态和不确定的危险区域中为消防员和消防车识别最快和最安全的疏散道路。开发的技术将转化为广泛的应用，如灾害（洪水，火灾，泥石流，恐怖主义）管理，其中需要快速搜索，监视和响应，而人工干预有限。该项目还将为未来的工程课程做出贡献，并将研究与教育结合起来，同时也让女性和代表性不足的少数民族学生参与进来，为K-12学生开发实践研究实验。该项目是对NSF Cyber-Physical Systems 20-该奖项反映了NSF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进行评估，被认为值得支持的搜索.

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.