Control of Multiple-UAV Conveying Slung Load With Obstacle Avoidance

Quadrotor Unmanned Aerial Vehicles (UAVs) are generally underactuated systems and when load is attached for transportation purposes, the system complexity increases. Therefore, need to appropriately control such becomes paramount as they usually navigate in cluttered environments. In this work, we conceptualize problem of cooperative tracking a Multi-agent UAV (MUAVLs) whereby each divided into global position local attitude subsystems. To ensure that formation maintained desired path, Neural Network Graph-theoretic Distributed Adaptive Control (NNGDAC) used subsystem with modified virtual force artificial potential field obstacle avoidance. Another Feedback Linearization (AFBL) controller also designed which verified by simulation results.