Self-resistance And Path Obstacle Avoidance Algorithm For Quadrotor Dron

In recent years,with the rapid development and application of UAVs in the fields of daily photography,map mapping,intelligence reconnaissance,mission search and rescue,and military defense,it is becoming more and more important for UAVs to have the functions of stable flight,autonomous obstacle avoidance and path planning.Research based on Active disturbance rejection,autonomous obstacle avoidance and path planning has become a research hotspot in the field of UAV applications.In view of the flight stability,safety and effectiveness of quadrotor UAV,this paper studies and optimizes the UAV stability control algorithm,autonomous obstacle avoidance algorithm and path planning algorithm,while improving its anti-jamming capability,a flight control algorithm for autonomous obstacle avoidance based on path planning is proposed,which realizes the UAV autonomous obstacle avoidance safely and effectively.the specific research contents are as follows:In order to solve the problems of slow response speed,poor adaptive ability and weak antiinterference ability of traditional UAV flight stability control algorithm,a cascade fuzzy PID flight control algorithm based on particle swarm optimization was proposed.By analyzing the UAV flight control principle,a UAV flight control model is established,On the basis of cascade fuzzy PID control,the iterative optimization ability of particle swarm optimization algorithm is used to determine the quantization factor and scale factor in the algorithm in real time,PID parameters are adjusted online through fuzzy control,so that each parameter in the smooth control is always optimized.The experimental results show that the flight control algorithm after particle swarm optimization has good control accuracy and stability,it can better improve the flight performance of the UAV,and meet the flight requirements of fast and efficient leveling.In order to solve the problem of low operation safety of quadrotor UAVs in complex environments,an autonomous obstacle avoidance algorithm for quadrotor UAVs is proposed to improve the adaptability and flexibility of obstacle avoidance of quadrotor UAVs during flight.By analyzing the principle of obstacle detection and obstacle avoidance,combined with the different properties of obstacles in the vertical direction,the complex obstacles in the environment are fitted with one-layer or multi-layer cylinder models to ensure that the obstacles are in any vertical position,the safe obstacle avoidance distance of the UAV is roughly the same;then the arc trajectory of safe obstacle avoidance is designed according to this model,and the obstacle avoidance is carried out until the defined obstacle avoidance end rule is met,so that the UAV can avoid obstacles autonomously.Through experimental analysis,it is verified that the quadrotor UAV can effectively avoid obstacles under the condition of relatively accurate waypoint tracking,and the flight trajectory is smooth,safe and efficient,which can greatly improve the speed and flexibility of UAV obstacle avoidance.In order to solve the problems of high energy consumption and many path inflection points of quadrotor UAVs when performing flight tasks,this paper starts with improving the quality of UAV flight paths,and proposes a path planning optimization for quadrotor UAVs based on RRT.By analyzing the environmental model and the constraints of the UAV’s own performance,the path planning of the quadrotor UAV is theoretically explained;At the same time,it optimizes the shortcomings of traditional RRT path planning,which improves the efficiency of path search,goal orientation and path smoothness.Experiments show that the RRT-based quadrotor path planning optimization algorithm can quickly generate smooth and high-quality paths for UAV flight.