Research On Based On Improved Sparrow Search Algorithm

Autonomous flight of UAVs is a difficult problem involving the intersection of multiple disciplines,and the difficulty lies in how to ensure that UAVs can safely complete the search of all target points on the predetermined routes,and to ensure the acquisition of the current position information of UAVs at each waypoint.UAV trajectory planning also has problems such as low efficiency,long time-consuming,and slow algorithmic computation speed,which is difficult to meet the requirements of UAV followable flight.Aiming at the above problems,this thesis takes quadrotor UAV as the research object,and the main research contents and results are as follows:(1)Aiming at the structural characteristics of the quadcopter UAV itself and the principle of map modelling,the quadcopter UAV trajectory planning model is constructed.This includes modelling the mission environment,setting UAV kinematic constraints and UAV trajectory planning cost indicators.After analysing and simulating these models,a complete UAV trajectory planning method is proposed.Simulated no-fly zones and abnormal weather zones are constructed in the map model,and the maximum range,minimum trajectory,minimum turning angle,and flight altitude are constrained according to the UAV kinematic constraints.In the UAV trajectory planning cost index,the three factors of fuel consumption cost of flight,altitude change cost and threat index are given weights to set the evaluation function of the trajectory planning.Finally,B-spline interpolation is used to smooth the planned path.(2)A trajectory planning method based on fused multi-strategy improved sparrow search algorithm is proposed.Firstly,Cubic chaotic mapping is used to initialise the population,which makes the population distribution more uniform and improves the diversity of sparrow population locations;secondly,the position information of individual sparrows is optimised,and the follower positions are updated using a positive cosine search strategy,and the nonlinearly decreasing parameter makes the search more detailed,which effectively reduces the probability of generating a local optimum;lastly,all sparrows and the optimal sparrow are updated using a firefly perturbation strategy to update their positions and improve their searchability,which improves the defects of the original search,makes the algorithm’s flexibility and search range increase,and inhibits the premature convergence of the population.The performance of the algorithm is verified by the benchmark test function,and two groups of simulation experiments are designed,using single-peak multidimensional test function and multi-peak multidimensional test function,respectively,to make comparisons with several typical algorithms,and verify the robustness and accuracy of the algorithm improvement from the three perspectives of convergence accuracy,global search speed and global stability.(3)A three-dimensional complex UAV mission environment is established,and the improved sparrow search algorithm is used for UAV trajectory planning,and terrain obstacles and threat zones are modelled.The simulation results show that the improved sparrow search algorithm is more efficient and has higher path smoothing compared to the sparrow search algorithm in solving UAV trajectory planning,and can obtain a highquality trajectory that satisfies the constraints,as well as the stability and safety of the planning requirements.(4)A matlab simulation platform for UAV trajectory planning and a hardware test platform based on Pixhawk flight controller are established,and the improved sparrow search algorithm is compared and analysed in the simulation platform and outdoor open real bad environment.Firstly,the overall scheme of UAV flight experiment is designed,the hardware platform is built and the relevant parameters of flight control are debugged.Secondly,according to the requirements of the flight experiment conditions in the outdoor environment,the design and implementation of the controller software is completed,including the main programme flow control and other contents.Finally,the designed UAV trajectory planning system was experimentally verified under single and multiple obstacle environments.The results of simulation experiments show that the improved sparrow search algorithm shows better results in UAV trajectory planning,and the feasibility and stability of the improved sparrow search algorithm are also verified in physical experiments.