Research On Fast Obstacle Avoidance Control Strategy Of Rotor UAV Swarm

With the advantages of wide spatial distribution,strong functional distribution and high system fault tolerance,quadrotor unmanned aerial vehicle swarm(quadrotor UAV swarm)has been widely used in various fields at present.However,the existing UAV swarm obstacle avoidance control technology has low obstacle avoidance efficiency in complex obstacle environment,especially for dynamic obstacles.To solve this problem,this paper takes the fast obstacle avoidance of swarm as the control goal,and designs a fast obstacle avoidance control strategy based on finite time consensus algorithm and artificial potential field(APF)obstacle avoidance algorithm to improve the obstacle avoidance efficiency of swarm in complex obstacle environment.Through computer simulation and physical prototype experiment,the avoidance efficiency of this strategy in complex obstacle environment is verified.The main research contents of this paper include the following parts:The first is to study the finite-time consensus formation control algorithm of UAV swarm.Aiming at the formation control accuracy and formation speed of UAV swarm,the formation model of the UAV swarm is established and the formation control targets of the swarm are analyzed.Then,according to the formation control objectives,based on the finite time consensus theory,the formation controller is designed from two parts: position control and attitude control.Then,the stability of the formation controller is analyzed by Lyapunov theory,and it is proved that it can achieve the formation control goal in a limited time.Finally,the effectiveness of the formation controller is verified through computer simulation.The second is to study the fast obstacle avoidance control strategy of UAV swarm.Firstly,the problems that need to be solved when the swarm avoids obstacles in a complex obstacle environment are analyzed from two aspects: the practical application requirements and the defects of traditional algorithms.Then,in order to solve these problems,by introducing the auxiliary potential field and dynamic potential field range about obstacle speed,the speed and efficiency of the algorithm for avoiding dynamic obstacles are improved from two aspects of time optimization and space optimization.At the same time,aiming at the defects of the algorithm itself,on the one hand,the local minimum and path jitter problems are solved by introducing dynamic disturbance and smoothing adjustment region.On the other hand,the target unreachable problem is improved by optimizing the trigger mechanism of virtual target points.Finally,a fast obstacle avoidance control strategy was designed based on the NSB method,and the priority model was used to coordinate the output of the formation and obstacle avoidance tasks to realize the fast obstacle avoidance control of the swarm.The third is to build a simulation test platform and a physical experiment platform to verify the performance of the fast obstacle avoidance control strategy.Firstly,a complex obstacle environment with multiple obstacles is built to verify the performance of the designed control strategy.The simulation results show that this strategy avoids the defects of the traditional algorithm,and the efficiency and success rate of avoiding dynamic obstacles are better than the traditional algorithm.After that,the physical prototype experiment platform was built to verify the practical application effect of the strategy,and the test data were analyzed to further illustrate the stability and applicability of the strategy.