Path Planning Algorithm on Large Scale Terrain Data Based on PRM with Non-Uniform Sampling Strategy

Path planning is a research hotspot in the field of geographic information. Many scholars research on path planning on road networks, but path planning in areas without road network has not been thoroughly studied. This paper aims to find lower-cost paths quickly on large scale digital terrain data. We proposed a method based on the PRM algorithm which incorporates a non-uniform sampling strategy to increase the possibility to find better paths with fewer sampling points. A post-optimization method is also suggested to optimize the final path. Experiments prove the effectiveness of our algorithm compared to classical PRM with the uniform sampling strategy.