Research On Uav’s Path Planning Algorithm For Forest Fire

In recent years,with the rapid development of scientific research in my country,Unmanned Aerial Vehicle(UAV)have been gradually applied to forest fire monitoring.At the same time,more and more scholars have begun to study the use of UAVs for forest fire fighting.In this paper,the following researches are carried out on UAV trajectory planning for forest fire monitoring and forest fire suppression:(1)Aiming at the trajectory planning of UAV inspection in the special mission area of the forest,two different full coverage search algorithms are proposed.When the mission area is obviously irregular,a patrol strategy based on the UAV’s operating heading is proposed,and the turning moment of the UAV is considered.This algorithm can reduce the number of turns of the UAV and the excess coverage of the track.When there are obstacles in the task area,the inspection strategy based on the simulated annealing algorithm is proposed.First,the grid method is used to process the environment,and the appropriate track points are selected for the UAV to convert the inspection task into a traveling salesman.Solve the problem,and finally use the simulated annealing algorithm to solve the problem.The simulation experiment results show that both of the proposed inspection strategies can plan the inspection trails for UAVs that can be used for forest fire monitoring.(2)In view of the trajectory planning problem of forest fire fighting,different algorithms are proposed for two different situations.When the difference in forest altitude is small,the trajectory based on the improved two-way rapid search random tree algorithm(RRT-connect)is proposed.Planning algorithm;when the forest altitude difference is large,a hybrid bat algorithm based on differential evolution is proposed for trajectory planning.Aiming at the plain forest,the UAV does not need to change the flight altitude frequently.Therefore,the problem is described as a two-dimensional environment of UAV trajectory planning,and the improved RRT-connect algorithm is used to plan the fire suppression trajectory for the UAV In the algorithm,first,by limiting the search range of the nearest neighbors,the construction speed of the search tree in the algorithm is improved,and a better trajectory can be quickly obtained;second,the trajectory is further optimized using the Dijkstra algorithm to find a better fire fighting voyage trace.For mountain forest fire fighting,if the UAV is allowed to fly in a plane at a higher position,it will consume more energy during take-off and landing.Therefore,the problem is described as a UAV trajectory planning in a three-dimensional environment,the trajectory will follow the ups and downs of the mountains,and the improved bat algorithm is used to solve this situation.Firstly,the differential evolution algorithm is used to solve the problem of "premature maturity" of the bat algorithm.Secondly,considering the threat of obstacles,a new fitness function is designed.The simulation results show that the algorithm proposed in this paper can plan a fire fighting trajectory that meets the requirements for the UAV,and provide a basis for the UAV to perform actual tasks.(3)Aiming at the problem that the planned trajectory cannot be directly used for UAV flight,different algorithms are used to smooth the trajectory.For the two-dimensional fire fighting trajectory,the minimum snap algorithm based on the flight corridor and the Bezier curve is used for smoothing.First,in view of the safety characteristics of the complete trajectory,the Bezier curve is used to restrict the flight corridor to ensure the safety of the entire flight trajectory;secondly,the minimum snap algorithm is used to add constraints to the trajectory segment to ensure that the UAV starts from the starting point.The position,speed and acceleration during the flight to the fire point are continuous,and the energy consumption is small.For the three-dimensional fire fighting trajectory,smooth processing is performed based on the characteristics of the third-order B-spline curve to ensure the continuous speed and acceleration of the UAV during the flight.(4)Experiment and verify the track for forest fire fighting on the indoor UAV—QDrone.Introduce the flying principle of UAV,indoor positioning system,experimental platform communication architecture and Simulink simulation module of QDrone.In this indoor experimental environment,firstly,it was verified on the indoor semi-simulation platform,and then the planned trajectory was further verified by the UAV.