Research On Collision And Obstacle Avoidance Control Method Of UAV Swarm

Quadrotor is a kind of unmanned aerial vehicle(UAV)which has attracted much attention in recent years.It can complete flight behavior by autonomous or remote control without direct pilot control.Multi UAVs coordinated autonomous formation flying is a frontier area in recent years.It can make full use of the limited resources to complete complex tasks.Collision avoidance is one of the key problems to be solved in UAV formation mission.It is the key to authorize UAV to enter general airspace by aviation supervision department,and also the key in the process of UAV swarm autonomy.The purpose of this project is to establish the theory and application method of autonomous cooperative control optimization of UAV swarm.We will provide scientific theoretical support for the breakthrough of intelligent autonomous cooperative control of UAV swarm and the promotion of swarming and intelligent development of UAV in China.First,considering the obstacle avoidance requirement of UAV swarm during actual flight,a control-oriented trajectory and attitude model of a quadrotor is established.To avoid the shortage of trajectory planning for each UAV which is used for traditional UAV swarm,a trajectory design strategy based on the central point of UAV swarm is proposed.Considering obstacle avoidance constraints,iterative regional inflation by semi-definite programming is proposed to design the safe flight area of UAV swarm,which ensures the obstacle avoidance flight of UAV swarm in multiconstraint environment.Then,considering the influence of uncertain model parameters and external disturbance on attitude control performance of quadrotors during flight,the distributed position controller,attitude solution algorithm and finite-time attitude controller based on disturbance compensation are used to realize the stable tracking of attitude commands in finite time.Furthermore,the validity of the proposed cooperative controller is verified by numerical simulation and the tracking accuracy is compared with the attitude controller based on cascade PID and sliding mode attitude controller based on twisting algorithm.It is verified that the finite-time attitude controller based on disturbance compensation has strong robustness and capacity of resisting disturbance under the premise of guaranteeing the tracking accuracy of the system.Finally,considering the obstacle avoidance requirement of UAV swarm during actual flight,a collision avoidance method based on potential function and reciprocal velocity obstacle is proposed.The collision avoidance method based on reciprocal velocity obstacle can avoid the shortage of trajectory planning for each UAV which is used for traditional UAV swarm by calculating the collision avoidance velocity in realtime and relying only on the position and velocity information of the adjacent aircraft.The collision avoidance of UAV is obtained by real-time optimization of the desired velocity of UAV.The traditional collision avoidance method based on potential function combined with the finite time attitude controller based on disturbance compensation can also eliminate some inherent limitations of potential function.Finally,the effectiveness of the cooperative controller and the collision and obstacle avoidance algorithm is verified by comprehensive numerical simulation and compared.