Research On UAV Horizontal Track Path Planning Algorithm

With the rapid development of UAV technology,UAVs are becoming more intelligent and the increasingly complex air environment has put forward new demands on UAV horizontal trajectory planning algorithms.The horizontal trajectory has to satisfy both the global route optimality and keep the local route away from obstacles to ensure flight safety.Therefore,this paper stipulates two aspects of research based on planning the global static path and local dynamic path of UAV horizontal trajectory under the same vertical altitude,and the main work of the paper is as follows.For how to reasonably plan the global optimal shortest horizontal trajectory of UAV in macro environment,this paper proposes a multi-level ant-state ant colony improvement algorithm based on the idea of hierarchy.The algorithm integrates the idea of artificial swarm hierarchy,divides the ant population of traditional ant colony algorithm into three levels,integrates the optimized pheromone update model,makes the individuals at each level update their pheromones based on different weighting operators,strengthens the guiding effect of dominant routes on algorithm planning,and dynamically balances the number of ant states at each level by introducing restriction factors and fitness operators.The local optimality seeking ability is strengthened by the fixed neighborhood optimization algorithm to avoid falling into the local optimum trap.For the problem that the approximate path of macroscopic planning may be diagonally through obstacles in microscopic environment,the local path should be further optimized so that the UAV can effectively avoid dynamic obstacles in complex environment,and this paper proposes a continuous dynamic planning algorithm based on improved D*LITE for two-dimensional paths in microscopic environment.The algorithm modifies the traditional Chebyshev estimation operator,introduces the idea of artificial potential field,improves the key-value calculation mechanism based on the gravitational operator,proposes a heuristic estimation operator,strengthens the cost of nodes relative to the global route,and optimizes the path using the directional contraindication matrix on this basis to avoid diagonally crossing the obstacle nodes,and smooths the planned route based on the redundant point deletion mechanism.The algorithm effectively reduces the frequency of dynamically updating the key values and allows dynamic planning of arbitrary mutated nodes under unknown circumstances.Finally,through corresponding comparison experiments,the results of this paper can show that the global path static planning algorithm proposed in this paper can reduce the number of iterations of the optimal solution and the running time by about 40% and 50%compared with the existing methods,and the local path dynamic planning algorithm proposed in this paper effectively avoids diagonal crossing obstacles compared with the existing improved D*LITE algorithm,and proposes a continuous dynamic planning mode compared with the existing algorithm and The running time is reduced by about 60%.Based on Qt simulation software,the above two chapters are applied to solve practical problems and verify the effectiveness of the UAV horizontal trajectory path planning algorithm research in this paper.