autopilot

The possibility of creating a computer control system for an unmanned aerial vehicle using remote cloud computing according to predefined scenarios from the user’s desktop is investigated. For this, an experimental setup was created, which includes a quadcopter, a personal computer with the Windows operating system, an on-board computer Raspberry-3 with the Linux operating system, a Pi Camera V2 camcorder, and a Pixhawk autopilot. To model the control and transmission of video images the own control programs and photo pursuit on a computer Raspberry-3 in Python are recorded.

The possibility of using a neural network to implement a system of avoidance of obstacles on the road has been investigated. The algorithms based on which such a system can work has been reviewed, also the principle of learning of the neural network has been considered. In order to implement investigation the simulator based on Unity and ML Agents has been developed. Using simulator the efficiency of education and this neural network in different configurations has been investigated.