Fast Route Planning on DEM Big Data with Cost Constraint Sampling

The current method of route planning on digital terrain model with no road network mainly adopts the algorithm of Dijkstra and A*. When the target area is large and the data resolution is high, the planning calculation will take a long time. In this paper, a fast route planning method for no road area based on cost constraint sampling is proposed. The Bresenham algorithm is used to design the cost calculation mode between sampling points, which solves the problem that the method cannot calculate the cost between non adjacent grid points on the digital elevation model, making it possible to obtain the routes based on sampling on the digital elevation model. At the same time, the sampling function is optimized in combination with the path traffic cost to improve the utilization of sampling points and reduce the computational scale of route planning, which greatly improve the speed of route planning. Experiments show that the proposed methods get the routes quickly, and has better route quality than the traditional uniform sampling PRM method. The proposed method has greater advantages in the rapid rough route planning in the area without road network.