UAV Path Planning Algorithm For Forest Patrol And Conservation

In recent years,with the continuous development of UAV technology,UAVs are gradually applied in the field of forest fire protection.It is worth noting that a path that meets certain performance indexes can significantly improve the operational efficiency of UAVs.Therefore,this paper studies the full-coverage path planning algorithm for forest patrolling and the point-topoint path planning algorithm for forest fighting,and the main research contents are:(1)A regional convex decomposition algorithm based on improved genetic algorithm is proposed for the regional convex decomposition problem.The turning flight of UAV consumes high energy,and too many turns will shorten the operation time of UAV.In this paper,the minimum width sum is used as the research direction,the concave point is used as the starting point of decomposition,the angle between an edge of the target region and the coordinate axis is used as the genetic gene,and the optimal decomposition angle of each concave point is obtained using the improved genetic algorithm.In the genetic algorithm,the random generation of genetic genes will reduce the efficiency of the algorithm iteration,in order to improve the iteration efficiency of the algorithm,the selection method of genetic genes is designed;the variation direction of the genetic algorithm has randomness,in order to get excellent variation direction,the concave point gene library is designed.Finally,the simulation experiments of region convex decomposition in single-machine target region and multi-machine target region are conducted,and the simulation results show that the decomposition effect of the improved genetic algorithmbased region convex decomposition algorithm proposed in this paper is not affected by the decomposition order,and the global minimum width sum can be obtained stably.(2)A forest patrol full-coverage path planning algorithm based on area convex decomposition is proposed for the forest patrol full-coverage path planning problem.The path length of covering sub-convex regions is fixed,but the coverage order and coverage entrances and exits between sub-regions are to be solved.In this paper,we design the sub-region connectivity method with the research direction of reducing the path length between sub-regions.Then,we design a method to select the entrances and exits of the sub-convex regions according to the coverage mode and flight orientation,and then use the entrances and exits as genetic factors to obtain the optimal coverage order and entrances of the sub-regions using an improved genetic algorithm.In the genetic algorithm,the optimal solution is retained in each natural selection in order to reach the optimal solution faster;the traditional crossover rule is easy to lead to the recoverage problem,and the sub-region crossover rule is designed in order to avoid the re-coverage problem;the traditional variation rule is difficult to achieve the sub-region coverage problem,and the sub-region gene pool is designed in order to avoid the omission coverage problem.In the single-machine area coverage simulation experiments and multi-machine area coverage simulation experiments,the simulation results show that the full-coverage path algorithm based on area convex decomposition proposed in this paper can shorten the flight path between subregions.(3)For the fire fighting point-to-point path planning problem,a fire fighting point-to-point path planning method based on the improved artificial potential field method is proposed.The artificial potential field method is attracted by the target point and approaches rapidly in the direction of the target point,but it is easy to fall into the dilemma of local minima and unreachability of the target point near the obstacle.In this paper,we propose an improvement method for the limitation of artificial potential field method,and propose a local repulsion adjustment method for the problem of unreachable target point near the obstacle,which only adjusts the repulsion in a certain range near the target point;we propose an escape method based on the obstacle model for the problem of easy to fall into the local minima,and select the virtual target point through the obstacle model to achieve the purpose of escaping the local minima.Finally,a simple forest environment is built using MATLAB and a simulation experiment of path planning with improved artificial potential field method is conducted.The simulation results show that the UAV can successfully escape from the local minima and reach the target point near the obstacles.