Integration of the author’s modification of the UAV obstacle avoidance algorithm into the ROS system

This paper presents the integration of a modified obstacle avoidance algorithm into the Robotic Operating System (ROS) for unmanned aerial vehicles (UAVs). The paper considers the interaction of three key components: Kalman filter, Dynamic System Modulation (DSM), and 3DVFH+ adaptive algorithm. These components provide accurate state estimation, adaptive control, and efficient trajectory planning of the UAV, which improves its maneuverability and safety in complex environments. Particular attention is paid to the implementation of component interactions through ROS, which contributes to the modularity and scalability of the system.