Abstract: |
Considering that buildings are irregularly distributed in cities, and the airspace structure is complex and diverse, low altitude logistics UAVs need to adapt to both simple and complex environments. In view of the poor adaptability of their path planning, how to establish a planning model and design an algorithm to solve the problem is the key. This paper proposes a UAV path planning algorithm based on improved spatial stratification. First, this paper designs a node model based on spatial layering. The hierarchical node structure can effectively save data storage space, and further filter the number of search nodes in complex environments combined with UAV constraints; Second, an adaptive initial planning level and estimated cost factor are designed for the hierarchical structure, which can automatically adjust the size of the classification and search speed according to the complexity and resolution of the environment, while meeting the requirements of low precision spatial fuzzy search and high precision spatial precise search. The simulation results on different complexity maps show that compared with D*Lite algorithm, the improved algorithm can save about 3% time to generate the path fitting the optimal solution in a simple environment, reduce the path length by 4% and improve the path smoothness by 20% in a complex map, which verifies the adaptability and feasibility of the algorithm. |