Multi-UAV Cooperative Obstacle Avoidance and Surveillance in Intelligent Transportation

Abstract

In intelligent transportation system, UAV surveillance plays an important role, and it has wide applications in traffic detection and order management, etc. However, the interference of extensive buildings and inaccessible regions in the urban environment directly lead to the failure of the surveillance task. Aiming at this issue, this paper proposes a method of multi-UAV UAV Cooperative Obstacle Avoidance and Surveillance (COAS). The ellipse tangent method is used to avoid obstacles for the interference of urban obstacles. Furthermore, taking into account the cooperation of multi-UAV formation, the cooperative model based on moving cost and formation stability is established. Due to the timeliness requirement of multi-UAV cooperative surveillance task, we use a sparrow search algorithm with fast convergence speed and strong optimization capability to solve the cooperative model. Finally, the simulation experimental results in an urban environment with obstacle information demonstrate the effectiveness of the proposed method in tackling the issues of cooperative obstacle avoidance and target surveillance.