Optimization Algorithm And Modeling Of UAV Flight In Irregular Farmland

With the continuous development of precision agriculture,smart agriculture and digital agriculture,the agricultural field has also ushered in the reform and innovation at the technical level.As a new type of intelligent equipment in the agricultural field,UAV provides a new way for the reform of agricultural technology.The use of unmanned aerial vehicles can effectively and nondestructively monitor crop growth,sowing,spraying,etc.,and can also detect pests and diseases according to aerial photographs,so as to carry out timely and accurate field management,reduce labor intensity,save production costs,improve production efficiency,and achieve high-quality green,increase and decrease production objectives.The most important thing for UAVs to operate in the field is route planning.The route path of UAVs is closely related to the safety,efficiency and quality of operations.Farmland is divided into regular farmland and irregular farmland according to the division of mathematical geometry.Targeted route planning according to different terrains helps to improve the accuracy and efficiency of optimization.Compared with regular farmland,the shape of the target area and the complexity of the environment of the irregular farmland are significantly increased.The traditional route planning algorithm is mainly aimed at regular farmland,and its optimal path and coating coverage are not sufficient to meet the accuracy and efficiency requirements of irregular farmland operations.Based on the constraints of UAV itself and external environment,this paper mainly studies the flight optimization algorithm and modeling of UAV route planning in the complex environment of irregular farmland.The main contents are as follows :(1)For the For the problem of modeling the space environment for UAV farmland inspection route planning,by comparing the projection principle and error analysis of Gaussian projection and UTM projection,Gaussian projection is selected as the projection method of farmland map;according to the advantages and disadvantages of different edge detection operators and comparing the operation results of simulation,the Canny operator is selected to determine the method of farmland boundary;through the characteristics of different spatial modeling methods,the grid map method is selected to determine the spatial modeling method of UAV route planning.The experimental results show that the above method can be effective to solve the spatial environment modeling problem of UAV inspection route planning.(2)For the inspection route planning of irregular farmland by UAV,by comparing the total path,turning times and overlap of the cattle farming method and the helical method,it is determined that the cattle farming method is the best operation method for full coverage.According to the specific conditions of the farmland,optimizing the cattle farming method of the grid map can effectively reduce the operation path and improve the operation efficiency.(3)Aiming at the problem of no obstacles in irregular farmland,combined with the rotation jam algorithm to realize the full coverage route planning of the UAV,through the MATLAB simulation experiment,the route time and the optimal rotation angle search time of different antipodal points as the base point are used as the route.It can provide a working path with the optimal working direction and the lowest flight cost.In view of the situation of irregular obstacles,by converting the pixel values into the form of xlsx array data,combined with the A-star algorithm,the obstacle avoidance of irregular obstacles is realized.The simulation results of MATLAB show that this method can effectively identify irregular obstacles.The boundary of the object is generated,and the optimal route map is generated to solve the complex problem of coverage and obstacle avoidance in the route process.(4)In view of the obstacle avoidance problem in UAV field fixed-point inspection route planning,the sparrow algorithm is improved,and the Cubic Map chaotic map,sine and cosine algorithm and firefly algorithm are introduced into the population optimization,follower and reconnaissance early warning of the sparrow search algorithm.The position update of adopts a variety of optimization methods,which can effectively avoid the original algorithm from falling into the local optimal solution,and improve the iterative efficiency and the accuracy of global optimization.The results of the simulation experiment based on the MATLAB benchmark function test show that the improved sparrow search algorithm can significantly improve the convergence speed and the accuracy of global optimization,which can reduce the actual operation energy consumption of the UAV and improve the operation efficiency.