Research On Trajectory Planning And Obstacle Avoidance Control Of Logistics UAV In Urban Low Altitude Environment

With the rapid development of electronic technology and control technology,rotor UAV has become more stable and intelligent.Under the development mode of "UAV + industry segmentation",it has become the research focus of academia and industry.For the logistics application of UAV in big city environment,how to obtain a safe,efficient an d energy-saving material distribution track has become the concern of many scholars.In this paper,this problem is divided into two sub problems: UAV three-dimensional space track planning and obstacle avoidance control.The traditional solutions are analyzed and improved,and the performance is compared and verified by simulation and physical experimentsFirstly,the influencing factors of the environmental conditions of the target city are analyzed,and the urban model is established;The solution of sam pling planning algorithms RRT(Rapid exploring Random Trees)and T-RRT(Transition based RRT)in path finding problem and the solution of genetic algorithm in task planning are analyzed;The motion mode of four rotor UAV is discussed and its motion model is established;The principle analysis,advantages and disadvantages of common environmental perception methods and artificial potential field(APF)for obstacle avoidance are summarized.Secondly,aiming at the path planning problem of UAV,a 3D global path planning algorithm EHT-RRT(Exploring Heuristic Transition based RRT)based on exploration,inspiration and transfer is proposed.The multi-layer heuristic cost exploration ball can comprehensively consider the path risk,length,deflection angle and height,and jointly affect the path finding direction;The local node slip strategy can make the path safer;The new path node expansion mechanism makes the planning quality higher and the solution speed faster.Simulation results show that compared with T-RRT,BT-RRT and T-RRT *algorithms with the same configuration,EHT-RRT algorithm can generate 3D path with shorter path,higher security and smoother.Then,the planning path is processed by bidirectional pruning,and optimized by B-spline curve.Based on genetic algorithm,considering the self weight and flight mileage of UAV,a new fitness function is proposed to make mission planning more stable and energy-saving.The potential field function of the artificial potential field method is improved to solve the problems of dead zone,oscillation and unreachable target of the traditional artificial potential field.Then,aiming at the obstacle avoidance control problem of UAV,the binocular depth camera and single line lidar are used for environmental perception,and the improved APF algorithm is used for local obstacle avoidance planning for possible unfamiliar obstacles.Simulation results show that this method can avoid unfamiliar obstacles and plan the target path again.GPS and monocular vision are used for positioning,and the parking and landing auxiliary graphics combined with concentric rings and two-dimensional codes are used to ensure the landing accuracy of logistics UAV,and the distance error is controlled at the centimeter level.Finally,integrating the solving process of track planning and obstacle avoidance control,the software in the loop simulation is carried out on the Ubuntu platform with the help of ROS robot operating system,gazebo 3D simulation engine and PX4 UAV simulation environment.At the same time,the logistics UAV experimental platform is built to verify the effectiveness of its functions such as track planning,visual landing and obstacle avoidance control.