Research on obstacles avoidance technology For UAV based on improved PTAM algorithm

When used in counter-terrorism and disaster rescue, UAVs may possibly fly in buildings. In an indoor closed environment, GPS signal may be blocked, which will make UAVs difficult to obtain their location. In addition, a complex indoor environment also brings challenges to the safety of flight. Therefore, it is necessary to identify complex environments and avoid obstacles in real-time. This paper introduces the PTAM algorithm to the UAV ground control module. To deal with poor illumination of indoor environment, less feature points and other issues, we improve the algorithm and design a self-adaptive map feature point generating mechanism, reducing the dependency of the algorithm on the number of feature points and illumination conditions. On this basis, this paper proposes an obstacle recognition algorithm and designs a warning mechanism for the ground control module. Finally, we use a small quad-rotor UAV to test this algorithm. The results show that the proposed method can provide warning to the obstacles during flight in unknown indoor environments with self-localization. The experiments demonstrate that this algorithm is effective in real-time, which has great significance to explore autonomous positioning and flight safety for UAVs in GPS denied environments.