| Chemical control is the main measure of pest control.With the common development of modern agriculture and science and technology,chemical control has gradually shifted from the traditional manual spraying of pesticides to UAV instead of human spraying in the field.In order to save economic cost and ensure food security,it is necessary to optimize the autonomous operation mode of UAV,so that it can complete autonomous operation with low energy consumption and high efficiency.Path planning is an important part of the autonomous operating system of plant protection UAV.Path planning is to plan the least consumption of pesticides,electricity,time and other operating paths according to the set work requirements and meet all control conditions.Therefore,in order to optimize the path of plant protection UAV,this paper combined with modern computer technology and optimization algorithm,based on Python language and Django framework,studied and developed the flight path optimization system of plant protection UAV.This paper focuses on the design and development of path optimization system for plant protection UAV as follows:(1)Research on the basic method of path planning for plant protection UAV.Firstly,a large number of literatures were consulted,and farmland plots were treated with grid method according to the operation characteristics of plant protection UAV.The walking strategy of plant protection UAV in the raster plot was designed to realize the full coverage path operation of the UAV in the plot of reciprocating rotation,and the operation simulation path diagram was obtained.The work area coordinate system is constructed to provide the computing environment for the subsequent optimization.Since the guarantee point is set at the origin of the coordinate system,after the path optimization objective is determined,a simple plan is proposed to make every return point fall on the bottom boundary of the operation area under all restrictions.When the operating area is too large,the result of unplanned is better than that of simple planning.Therefore,an optimization algorithm is proposed to plan the path of plant protection UAV.(2)Research on path planning algorithm of plant protection UAV.With the distance of each plant protection operation as the variable,and the shortest time of non-plant protection operation such as round-trip flight distance,battery replacement and liquid medicine filling as the objective,the function was constructed.Particle swarm optimization algorithm and gravity search algorithm were used to optimize the number and location of return points.The path planning method based on two optimization algorithms proposed in this paper is tested by examples,and it is found that the output results of particle swarm optimization algorithm are better than that of gravitational search algorithm,so particle swarm optimization algorithm is selected as the optimization algorithm of this system.Compared with simple planning and no planning,the total distance of non-plant protection operation was reduced by 15%and 79%,and the time of non-plant protection operation was reduced by 21%and 48%,respectively.This method also applies to irregular areas.The irregular operation area in the shape of right angle trapezoid was selected,with a length of 100m on top and 137m on bottom and a height of 740m on bottom.In this irregular operation area,the results of PSO based planning reduced the distance of non-plant protection operation by 13%and 78%,and the time of non-plant protection operation by 19%and 49%,respectively,compared with the results of simple planning and no planning.The above two examples verify the practicability and feasibility of the proposed path planning method.(3)Design and implementation of path optimization system for plant Protection UAV.After the path planning method proposed in this paper was verified by an example,the path optimization system of plant protection UAV was developed and implemented based on Python language using Vue framework and Django framework.The system is divided into six modules.The other modules can be unlocked only after the user registers and logs in.The system introduction module allows users to have a brief understanding of the system,and the plant protection UAV classification module can provide users with the choice of plant protection UAV types.The function of the input module interface is to transmit the land plot information and UAV parameters input by users to the back-end optimization model.The core part of the system is the output module.After the user inputs parameters,the output module can display the optimized simulation path diagram of plant protection UAV,compare the data of the three planning methods,and provide the optimized location and coordinates of the return point.The path optimization system of plant protection UAV can realize accurate path optimization of plant protection UAV,and can import the path optimization diagram into the control system of plant protection UAV to realize independent operation.It can also help UAV operators conduct data analysis and guide the precise operation of plant protection UAV,which plays an important reference role in improving the operation efficiency of plant protection UAV in the future. |
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