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

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Autonomous Target Tracking Of A Quadrotor UAV Using Monocular Visual-Inertial Odometry

Unmanned Aerial Vehicle (UAV) has been finding its ways into different applications. Hence, recent years witness extensive research towards achieving higher autonomy in UAV. Computer Vision (CV) algorithms replace Global Navigation Satellite System (GNSS), which is not reliable when the weather is bad, inside buildings or at secluded areas in performing real-time pose estimation. Thecontroller later uses the pose to navigate the UAV. This project presents a simulation of UAV, in MATLAB & SIMULINK, capable of autonomously detecting and tracking a designed visual marker. Referring to and improving the state-of-the-art CV algorithms, there is a newly formulated approach to detect the designed visual marker. The combination of data from the monocular camera with that from Inertial Measurement Unit (IMU) and sonar sensor enables the pose estimation of the UAV relative to the designed visual marker. A Proportional-Integral-Derivative (PID) controller later uses the pose of the UAV to navigate itself to be always following the target of interest