Small UAVs with autonomous avoidance using humanlike thoughts

摘要

With the national low-altitude airspace open, small UAVs are widely used in urban space. But there are dense obstacles and complex electromagnetic waves, producing serious challenges for UAVs' safety. In the region UAV loses track, it should have the ability to fly automatically and to escape from this region. By imitating the human-beings' escaping thoughts, five flying principles(exploring principle, optimal path principle, dead zone escaping principle, neighbor gather principle and roominess tending principle) are proposed based on the combination of breadth first algorithm, exploring random tree structure, so a humanoid algorithm is constructed on the basis of the five principles. The contrastive simulation results have verified that the proposed method in this paper can not only avoid the problem in traditional algorithms that obstacles simplifying is not applicable to dense environment, but also greatly boost exploring efficiency by applying exploring random tree structure to breadth first algorithm.