|
|
Safe Drone Reconnaissance Based on Smart Trajectory Following
Ferencz, Adam ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
Drone pilots often have to keep an eye on multiple things at once while performing a reconnaissance mission. First and foremost, the pilot has to keep an eye on the drone, but in addition to that, he or she is also observing something, keeping an eye on the image, the drone's orientation, speed, and obstacles. The goal of this work is to create an assistance algorithm that makes it easier for the pilot to watch the safe position of the drone. The work presents a novel method revising the pilot's commands to keep the drone "safely close" to a predefined flight path. This allows the pilot to focus more on accomplishing the mission objectives rather than directly and safely controlling the drone. The output of this work is a novel method and its experimental application that has been user-tested. For testing, an AirSim simulator was integrated into the system, in which the user completes a mission first without correction enabled and then with it. In the user tests, the goal was to successfully complete the reconnaissance mission. Pilots spent 55 % of the time outside the defined safe area when flying without correction, and only 5 % when flying with the assistant. Test users reported that the solution helped them most in maintaining altitude and staying on the centre of the path.
|
|
|
Crowd Density Estimation from a Photo
Ferencz, Adam ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
The aim of this thesis is to develop an aplication estimating the total number of people at a demonstration or at other public events. Input is a serie of photos from a drone or some other photos. The output are couloured maps according to people density in the place. Photos are placed in a topological map. Convolutional neural network MCNN is used for the crowd counting, which can generate a density map from the photo. Special method was proposed to correct the total amount of counted people when photographs overlap. The application is divided into server and web client. The server part generates density maps, saves data and runs an overlap correction algorithm. Client handles user inputs and provides an interactiv map with visualization.
|
|
|
Safe Drone Reconnaissance Based on Smart Trajectory Following
Ferencz, Adam ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
Drone pilots often have to keep an eye on multiple things at once while performing a reconnaissance mission. First and foremost, the pilot has to keep an eye on the drone, but in addition to that, he or she is also observing something, keeping an eye on the image, the drone's orientation, speed, and obstacles. The goal of this work is to create an assistance algorithm that makes it easier for the pilot to watch the safe position of the drone. The work presents a novel method revising the pilot's commands to keep the drone "safely close" to a predefined flight path. This allows the pilot to focus more on accomplishing the mission objectives rather than directly and safely controlling the drone. The output of this work is a novel method and its experimental application that has been user-tested. For testing, an AirSim simulator was integrated into the system, in which the user completes a mission first without correction enabled and then with it. In the user tests, the goal was to successfully complete the reconnaissance mission. Pilots spent 55 % of the time outside the defined safe area when flying without correction, and only 5 % when flying with the assistant. Test users reported that the solution helped them most in maintaining altitude and staying on the centre of the path.
|
|
|
Crowd Density Estimation from a Photo
Ferencz, Adam ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
The aim of this thesis is to develop an aplication estimating the total number of people at a demonstration or at other public events. Input is a serie of photos from a drone or some other photos. The output are couloured maps according to people density in the place. Photos are placed in a topological map. Convolutional neural network MCNN is used for the crowd counting, which can generate a density map from the photo. Special method was proposed to correct the total amount of counted people when photographs overlap. The application is divided into server and web client. The server part generates density maps, saves data and runs an overlap correction algorithm. Client handles user inputs and provides an interactiv map with visualization.
|
guest ::
