Obstacle Avoidance Manager for UAVs Swarm

Abstract

Multi-Robot Systems for a swarm of autonomous UAVs are critical in providing essential solutions to numerous applications. However, working in complex environments requires higher levels of safety in navigation. One of the problems is the detection and avoidance of static and dynamic obstacles that appear in the UAVs paths.In this paper, two complementary methods are presented; to provide safe autonomous navigation of a swarm of UAVs. On the one hand, a method based on the Velocity Obstacle (VO) is responsible for avoiding collisions between the UAVs of the swarm by decreasing the velocity of the UAVs when they approach the same location. This method has the advantage of reducing the use of UAV resources and computational time. On the other hand, a method based on Light Detection and Ranging (LiDAR) information and Probabilistic Roadmaps (PRM) allows detecting dynamic obstacles appear in the path, exploring the environment in search of alternative paths, and finally establishing the one that minimizes the distance, and allows reaching a location avoiding the detected obstacles. The proposed methods have been tested and validated in simulation environments; as a previous step to their implementation in real UAVs. Moreover, the obtained results show the robustness and the efficiency of the system in detecting and avoiding the possible collisions.