An approximate of the cost-to-go map on rough terrains

Abstract

The Roughness based Navigation Function (RbNF) is a numerical map that estimates the mobility measure (cost-to-go) from each terrain location toward the goal position. This paper compares the RbNF and the optimal cost-to-go map in terms of computational burden and solution quality. When the terrain is very large and obtaining the optimal cost-to-go map is computationally too expensive, the RbNF is shown to be able to compute an approximate solution much more quickly. As an application example, in which the RbNF is shown to be a powerful tool, the paper considers a Mars rover mission that finds the possible landing site using a mobility cost-to-go map constructed from a Mars terrain data.