| As UAV-related technologies become more and more mature and intelligent,UAVs have been widely used in various fields.However,when UAVs are performing tasks,how to effectively carry out autonomous trajectory planning has become a current research hotspot,so it is especially important to develop an efficient trajectory planning algorithm.In this paper,the UAV trajectory planning algorithm is studied,firstly,the A* algorithm and dynamic window approach in two-dimensional are improved for the problems of many trajectory turning points and redundant trajectory length,then the sparrow search algorithm in three-dimensional space is improved for the problem of easily falling into local optimum,and finally the UAV autonomous trajectory planning system is built based on Pixhawk flight controller and experimental testing and analysis are conducted.The work and innovations in this paper are mainly as follows:1.Aiming at the problem of two-dimensional track planning,a dynamic track planning algorithm based on improved A* and IDWA(Improved Dynamic Window Approach)is integrated.Firstly,the search mechanism is extended by the improved A*algorithm to solve the problems of more turning points and redundant trajectory length in the trajectory planning process.Secondly,the environmental obstacle distribution rate is introduced into the weighting coefficient of the azimuth evaluation function of the dynamic window approach to solve the problem that the algorithm is easy to fall into the local optimum.The simulation results show that the improved dynamic window approach reduces the track length by 18.43% and the planning time by 56.28%.Finally,an evaluation function is redesigned based on the improved A* algorithm,so that the UAV can avoid obstacles while ensuring optimal global trajectory.2.Aiming at the trajectory planning problem of UAV in three-dimensional space,an improved sparrow search algorithm is used to solve the trajectory planning problem,and established a three-dimensional space planning model of UAV.Firstly,the population is initialized by Logistic-tent chaotic mapping;then the location and number of individuals in the population are adaptively changed during the finder-vigilant position update to speed up the convergence of the algorithm at a later stage;finally,the Gaussian-Cauchy mutation strategy is used to improve the search capability of the algorithm.In this paper,five other comparison algorithms are chosen to verify the effectiveness of the improved sparrow search algorithm from the test function and Wilcoxon rank sum test respectively,and finally the improved algorithm is used for UAV 3D trajectory planning.The simulation results show that the optimization accuracy of the EMSSA algorithm is improved by 4.11%compared with the ISSA algorithm,and 9.51% compared with the SSA algorithm.3.Through the research on the above track planning algorithm,a UAV autonomous track planning system based on Pixhawk flight controller is designed in terms of software,hardware and data communication,and the stability and reliability of the flight control platform selected in this paper were verified from attitude control and position control loops,and finally the trajectory planning tests were conducted in the simulation platform and outdoor environment respectively.The test results show that the quadrotor UAV trajectory planning system designed in this paper can effectively perform autonomous trajectory planning and obstacle avoidance flight. |
