Autonomous Compact Monitoring of Large Areas Using Micro Aerial Vehicles with Limited Sensory Information and Computational Resources

In this paper, a new approach for autonomous real-time monitoring of large areas using small unmanned areal vehicles with limited sensory and computational resources is proposed. Most of the existing solutions of area monitoring require large aerial vehicles to be equipped with a list of expensive sensors and powerful computational resources. Recent progress in Micro Aerial Vehicles (MAVs) allows us to consider their utilization in new tasks, such as the considered compact monitoring, which are dedicated to large well-equipped aerial vehicles so-far only. The proposed solution enables online area monitoring using MAVs equipped with minimal sensory and computational resources and to process the obtained data only with cell phones capabilities, which considerably extends application possibilities of the drone technology. The proposed methodology was verified under various outdoor conditions of real application scenarios with a simple autonomous MAV controlled by the onboard model predictive control in a robotic operation system (ROS), while the user interface was provided on a standard smartphone with Android OS.