An Unmanned Aerial System for Prescribed Fires

Prescribed fires can lessen wildfire severity and control invasive species, but some terrains may be difficult, dangerous, or costly to burn with existing tools. This thesis presents the design of an unmanned aerial system that can ignite prescribed fires from the air, with less cost and risk than with aerial ignition from a manned aircraft. The prototype was evaluated in-lab and successfully used to ignite interior areas of two prescribed fires. Additionally, we introduce an approach that integrates a lightweight fire simulation to autonomously plan safe flight trajectories and suggest effective fire lines. Both components are unique in that they are amenable to input from the system’s sensors and the fire crew. A preliminary study confirms that such inputs improve the accuracy of the fire simulation to better counter the unpredictability of the target environment. Advisors: Carrick Detweiler and Sebastian Elbau

The implementation and evaluation of a black carbon aerosol sampler used on an unmanned aircraft during the prescribed fire experiment RxCADRE

Thesis (M.S.) University of Alaska Fairbanks, 2014Black carbon (BC) aerosols impact the earth's climate by absorbing solar radiation in the atmosphere and depositing on ice surfaces and lowering the albedo of those surfaces. Black carbon aerosols have been widely studied; however, using small unmanned aircraft systems (UAS) for the airborne study of the vertical and horizontal concentrations of BC is an emerging field. Using UAS to study BC poses some challenges due to size and weight restrictions of the aircraft, as well as issues that arise when adapting ground based instrumentation for use on different aircraft. University of Alaska Fairbanks researchers successfully integrated and flew a microAeth AE-51 on a Boeing ScanEagle to measure the concentration of BC and other absorbing and scattering particles in the smoke plume from a prescribed fire experiment, RxCADRE, conducted at Eglin AFB, FL, during October and November 2012. The ScanEaglemounted microAeth successfully collected black carbon aerosols in the smoke plume. The optical particle sizing and mass loadings from an optical particle counter disagreed with the results from the microAeth, which measures absorbing aerosols. The microAeth was tested in the laboratory-using two optical particle sizers to verify the sizes and concentrations of laboratory-generated aerosols entering the instrument and determine the capabilities and limits of the instrument. The optical particle counters were used in other applications as well showing the versatility of the instruments in extreme conditions

FIRE SUPPRESSION AND IGNITION WITH UNMANNED AERIAL VEHICLES

An unmanned aerial vehicle ( UAV ) can be configured for fire suppression and ignition . In some examples , the UAV includes an aerial propulsion system , an ignition system , and a control system . The ignition system includes a container of delayed - ignition balls and a dropper configured , by virtue of one or more motors , to actuate and drop the delayed - ignition balls . The control system is configured to cause the UAV to fly to a site of a prescribed burn and , while flying over the site of the prescribed burn , actuate one or more of the delayed - ignition balls . After actuating the one or more delayed - ignition balls , the UAV drops the actuated one or more delayed - ignition balls from the UAV onto the site of the prescribed burn

Design, Testing and Evaluation of Robotic Mechanisms and Systems for Environmental Monitoring and Interaction

Unmanned Aerial Vehicles (UAVs) have significantly lowered the cost of remote aerial data collection. The next generation of UAVs, however, will transform the way that scientists and practitioners interact with the environment. In this thesis, we address the challenges of flying low over water to collect water samples and temperature data. We also develop a system that allows UAVs to ignite prescribed fires. Specifically, this thesis contributes a new peristaltic pump designed for use on a UAV for collecting water samples from up to 3m depth and capable of pumping over 6m above the water. Next, temperature sensors and their deployment on UAVs, which have successfully created a 3D thermal structure map of a lake, contributes to mobile sensors. A sub-surface sampler, the “Waterbug” which can sample from 10m deep and vary buoyancy for longer in-situ analysis contributes to robotics and mobile sensors. Finally, we designed and built an Unmanned Aerial System for Fire Fighting (UAS-FF), which successfully ignited over 150 acres of prescribed fire during two field tests and is the first autonomous robot system for this application. Advisers: Carrick Detweiler and Carl Nelso

Fire Immediate Response System Workshop Report

California's recent wildfires, exacerbated by extreme weather conditions, have focused the nation's attention on the problem of managing fire at the wildland urban interface. With the goal of understanding how new or re-imagined technologies could improve early fire detection and response, the Gordon and Betty Moore Foundation hosted a "Fire Immediate Response System" workshop (April 24 -26, 2019). The workshop identified the following priorities and recommendations, which are described in detail in the report.* Develop a shared, integrated platform for diverse sources of data, intelligence and information* Conduct new wildfire risk assessments with high-resolution mapping technologies* Improve scientific understanding of "megafires" through retrospective analysis* Enhance fire behavior models and associated inputs for real-time prediction* Perform a cost-benefit analysis of investment in solutions vs. reactive management* Target investments in the development and adoption of new technologies* Expand multi-stakeholder dialogue, collaboration and actio

Reliability, Safety, and Performance for Two Aerospace Revolutions - UAS/ODM and Commercial Deep Space

Aerospace is in the midst of a renaissance, expanding on both the air and space side into major new commercial areas including unmanned air systems (UAS), on demand mobility (ODM), personal air vehicles (PAV), and commercial deep space. These new areas require, in the initial planning, consideration of new safety, reliability, and in some cases, enabling performance approaches for viability. For example, due to their huge numbers, if current accident rates prevail, UAS/ODM/PAV aircraft could crash at an unacceptable rate, causing life and property damage. Also, if humans in commercial space activities have serious health issues and/or there are unacceptable rocket viability issues/crash rates, these new, major markets (order of 1 trillion dollars per year) could be rapidly curtailed until agreeable and effective changes are instituted, producing additional expense, delay, and reduced revenue. This report addresses such safety and reliability issues and includes: performance enhancement possibilities such as an enabling Air Traffic Control System (ATC), crash proof vehicles, increased range for aero, space debris removal, and human health for space

EXAMINING ASPEN EXPANSION FROM BEFORE AND AFTER PRESCRIBED BURNING IN A NATIVE FESCUE GRASSLAND THROUGH GEOSPATIAL TECHNIQUES

Native fescue (Fescue spp.) grasslands of the Intermountain West have become increasingly scarce due to the advent of modern agriculture, the loss of Indigenous people’s land management practices, modern wildfire management and the extirpation of bison (Bison bison bison). Native grassland is a biodiversity hot-spot, is significant for carbon sequestration, and essential to many species of flora and fauna that occur in the ecosystem. Our study site, on the Rocky Mountain Front in Waterton Lakes National Park, Alberta Canada, consists of 30 discrete aspen stands (Populous tremuloides) which are encroaching on this declining shortgrass fescue grassland. Parks Canada is attempting to suppress aspen expansion and improve fescue prairie through ecological restoration by instituting prescribed burns and elk (Cervus elaphus) browse. Prescribed burns will decrease woody vegetation through adult aspen stem mortality while stimulating regeneration, which is subsequently browsed by elk. The park has a wolf pack (Canis lupus) that preys primarily on the elk, thereby affecting aspen stem recruitment spatially. These dynamics create a natural laboratory for examining the interaction of fire, elk and wolves that impact the aspen/grassland dynamics. We measured the aspen stand structure before and after a prescribed burn set in spring of 2017 to determine the change in aspen stand area from before to after the burn. We measured aspen stands before the prescribed burn during the summer of 2016 via GNSS handheld mapping units. We collected post-burn measurements in summer 2017 via unmanned aerial system (UAS). We also conducted ground measurements for a subset of aspen stands in 2017 to ground-truth the aerial photography data. We used knowledge Engineer (KE) in Erdas Imagine for classifying the UAS imagery and then created polygons in ArcGIS to analyze the data from before and after prescribed burning. We also digitized all aspen stand layers from the UAS imagery through the heads-up digitization technique and used these data to compare the aspen stands from before to after prescribed burning. Aspen stand area did not decline at a statistically significant level for any layers we measured: canopy, regeneration, and shrub expansion before and after prescribed burning. We did see an observational decline in the total aspen canopy area

Design, Testing and Evaluation of Robotic Mechanisms and Systems for Environmental Monitoring and Interaction

Unmanned Aerial Vehicles (UAVs) have significantly lowered the cost of remote aerial data collection. The next generation of UAVs, however, will transform the way that scientists and practitioners interact with the environment. In this thesis, we address the challenges of flying low over water to collect water samples and temperature data. We also develop a system that allows UAVs to ignite prescribed fires. Specifically, this thesis contributes a new peristaltic pump designed for use on a UAV for collecting water samples from up to 3m depth and capable of pumping over 6m above the water. Next, temperature sensors and their deployment on UAVs, which have successfully created a 3D thermal structure map of a lake, contributes to mobile sensors. A sub-surface sampler, the “Waterbug” which can sample from 10m deep and vary buoyancy for longer in-situ analysis contributes to robotics and mobile sensors. Finally, we designed and built an Unmanned Aerial System for Fire Fighting (UAS-FF), which successfully ignited over 150 acres of prescribed fire during two field tests and is the first autonomous robot system for this application. Advisers: Carrick Detweiler and Carl Nelso

Co-Regulated Consensus of Cyber-Physical Resources in Multi-Agent Unmanned Aircraft Systems

Intelligent utilization of resources and improved mission performance in an autonomous agent require consideration of cyber and physical resources. The allocation of these resources becomes more complex when the system expands from one agent to multiple agents, and the control shifts from centralized to decentralized. Consensus is a distributed algorithm that lets multiple agents agree on a shared value, but typically does not leverage mobility. We propose a coupled consensus control strategy that co-regulates computation, communication frequency, and connectivity of the agents to achieve faster convergence times at lower communication rates and computational costs. In this strategy, agents move towards a common location to increase connectivity. Simultaneously, the communication frequency is increased when the shared state error between an agent and its connected neighbors is high. When the shared state converges (i.e., consensus is reached), the agents withdraw to the initial positions and the communication frequency is decreased. Convergence properties of our algorithm are demonstrated under the proposed co-regulated control algorithm. We evaluated the proposed approach through a new set of cyber-physical, multi-agent metrics and demonstrated our approach in a simulation of unmanned aircraft systems measuring temperatures at multiple sites. The results demonstrate that, compared with fixed-rate and event-triggered consensus algorithms, our co-regulation scheme can achieve improved performance with fewer resources, while maintaining high reactivity to changes in the environment and system

Defensive swarm: an agent-based modeling analysis

Security at remote military bases is a difficult, yet critical, mission. Remote locations are generally closer to enemy combatants and farther from supporting forces; the individuals charged with defending the bases do so with less equipment. These locations are also usually reliant on air-resupply missions to maintain mission readiness and effectiveness. This thesis analyzes how swarms of small autonomous unmanned aerial vehicles (UAVs) could assist in defensive operations. To accomplish this, I created an agent-based computer simulation model, which creates a tactical problem (enemies attempting to attack or infiltrate a notional base) that a swarm of UAVs attempts to defend against. Results indicate that a swarm can effectively deter 95% of attackers if each UAV is responsible for covering no more than 0.18 square miles and at least 40% of the UAVs are armed. I conclude that UAVs are an excellent addition to base defense and are particularly helpful at remote outposts with less organic capability (limited field of view, defensive assets, etc.). While this research deals specifically with countering a threat to a central base, the algorithms for swarm dynamics could be applied to future problems in mobile convoy or aircraft defense, and even peacetime applications like search and rescue.http://archive.org/details/defensiveswarmng1094556777Major, United States Air ForceApproved for public release; distribution is unlimited