Unmanned Aerial Systems for Wildland and Forest Fires

Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

Coordinated Control of UAVs for Human-Centered Active Sensing of Wildfires

Fighting wildfires is a precarious task, imperiling the lives of engaging firefighters and those who reside in the fire's path. Firefighters need online and dynamic observation of the firefront to anticipate a wildfire's unknown characteristics, such as size, scale, and propagation velocity, and to plan accordingly. In this paper, we propose a distributed control framework to coordinate a team of unmanned aerial vehicles (UAVs) for a human-centered active sensing of wildfires. We develop a dual-criterion objective function based on Kalman uncertainty residual propagation and weighted multi-agent consensus protocol, which enables the UAVs to actively infer the wildfire dynamics and parameters, track and monitor the fire transition, and safely manage human firefighters on the ground using acquired information. We evaluate our approach relative to prior work, showing significant improvements by reducing the environment's cumulative uncertainty residual by more than $10^2$ and $10^5$ times in firefront coverage performance to support human-robot teaming for firefighting. We also demonstrate our method on physical robots in a mock firefighting exercise

Using a Semi-autonomous Drone Swarm to Support Wildfire Management – A Concept of Operations Development Study

This paper provides insights into a human factors-oriented Concept of Operations (ConOps), which can be applied for future semi-autonomous drone swarms to support the management of wildfires. The results provide, firstly, an overview of the current practices to manage wildfires in Finland. Secondly, some of the current challenges and future visions about drone usage in a wildfire situation are presented. Third, a description of the key elements of the developed future ConOps for operating a drone swarm to support the combat of wildfires is given. The ConOps has been formulated based on qualitative research, which included a literature review, seven subject matter expert interviews and a workshop with 40 professionals in the domain. Many elements of this ConOps may also be applied to a variety of other swarm robotics operations than only wildfire management. Finally, as the development of the ConOps is still in its first stage, several further avenues for research and development are proposed

Monitoring and Cordoning Wildfires with an Autonomous Swarm of Unmanned Aerial Vehicles

Unmanned aerial vehicles, or drones, are already an integral part of the equipment used by firefighters to monitor wildfires. They are, however, still typically used only as remotely operated, mobile sensing platforms under direct real-time control of a human pilot. Meanwhile, a substantial body of literature exists that emphasises the potential of autonomous drone swarms in various situational awareness missions, including in the context of environmental protection. In this paper, we present the results of a systematic investigation by means of numerical methods i.e., Monte Carlo simulation. We report our insights into the influence of key parameters such as fire propagation dynamics, surface area under observation and swarm size over the performance of an autonomous drone force operating without human supervision. We limit the use of drones to perform passive sensing operations with the goal to provide real-time situational awareness to the fire fighters on the ground. Therefore, the objective is defined as being able to locate, and then establish a continuous perimeter (cordon) around, a simulated fire event to provide live data feeds such as e.g., video or infra-red. Special emphasis was put on exclusively using simple, robust and realistically implementable distributed decision functions capable of supporting the self-organisation of the swarm in the pursuit of the collective goal. Our results confirm the presence of strong nonlinear effects in the interaction between the aforementioned parameters, which can be closely approximated using an empirical law. These findings could inform the mobilisation of adequate resources on a case-by-case basis, depending on known mission characteristics and acceptable odds (chances of success)

Local Government Policy and Planning for Unmanned Aerial Systems

This research identifies key state and local government stakeholders in California for drone policy creation and implementation, and describes their perceptions and understanding of drone policy. The investigation assessed stakeholders’ positions, interests, and influence on issues, with the goal of providing potential policy input to achieve successful drone integration in urban environments and within the national airspace of the United States. The research examined regulatory priorities through the use of a two-tiered Stakeholder Analysis Process. The first tier consisted of a detailed survey sent out to over 450 local agencies and jurisdictions in California. The second tier consisted of an in-person focus group to discuss survey results as well as to gain deeper insights into local policymakers’ current concerns. Results from the two tiers of analysis, as well as recommendations, are provided here