Collision Avoidance for a Fence Inspecting Drone Operating at an Airport

Sammanfattning: Many important facilities are surrounded by security fences that need to be regularly inspected for damage. To automate this task it has been proposed to use a drone equipped with a camera. The images taken by the camera would be analyzed using deep learning and thereby no human labor would be required except for when there are damages that need to be repaired. While flying autonomously along the fence it is important that the drone does not collide with unexpected obstacles. The aim of this project is to propose a suitable algorithm to avoid collisions during the inspection mission. To gather information about the environment and detect potential obstacles a stereo camera is used. Since the purpose of the drone is to capture images of the fence one of the criteria for evaluating the method is that the avoidance maneuvers should not cause the drone to miss more of the fence than necessary. The method chosen is based on the concept of collision cones. The idea is to approximate a bounding box around the obstacle and create a cone with the outline of the bounding box as the base and the drone position as the top point. The drone is restricted from flying in a direction inside the cone and is thereby forced to find a path around the obstacle. The algorithm is implemented and tested in simulation. From the simulation results, it is concluded that the algorithm is able to prevent collisions. Also, conclusions about how the parameter values should be chosen for the real drone are made.