A fine-grained navigation network construction method for urban environments

Fine-grained navigation is becoming increasingly demanded in urban areas. However, current navigation software fails to provide accurate paths on grounds without roads (GWR) like residential communities, squares, parks, etc. In this work, a method for the construction of fine-grained navigation networks for urban environments is developed. Remote sensing images are used to estimate the traversability of GWR. A Voronoi diagram that conforms to important shapes, such as buildings, is created for the spatial partitioning of GWR into meaningful atomic regions. A computational model of traversability is constructed based on the Voronoi diagram to construct the navigation mesh of GWR. A fine-grained navigation network is then generated by integrating the GWR navigation mesh and urban road networks. Two experiments are performed to evaluate the effectiveness and efficiency of the proposed method. The results show that the proposed method performs well in both the representation of traversability in GWR and fine-grained path planning in urban areas. Moreover, the integration of the fine navigation mesh and urban road networks proves that such a method has the potential to provide finegrained navigation services.

Automated summary

This study proposes a method for constructing fine-grained navigation networks in urban environments. It uses remote sensing images to estimate the traversability of grounds without roads and integrates this information with the urban road networks to generate a fine-grained navigation network. The experiments show that the proposed method effectively represents the traversability of grounds without roads and performs well in fine-grained path planning in urban areas.